Model Name | Model (API Parameter) | OpenAI Chat Completions | OpenAI Responses | Anthropic |
DeepSeek-V4-Flash (Vendor Direct) | deepseek-v4-flash-202605 | ✅ | ❌ | ✅ |
DeepSeek-V4-Pro (Vendor Direct) | deepseek-v4-pro-202606 | ✅ | ❌ | ✅ |
DeepSeek-V4-Flash | deepseek-v4-flash | ✅ | ❌ | ✅ |
DeepSeek-V4-Pro | deepseek-v4-pro | ✅ | ❌ | ✅ |
Deepseek-v3.2 | deepseek-v3.2 | ✅ | ❌ | ✅ |
GLM-5.1 | glm-5.1 | ✅ | ❌ | ✅ |
GLM-5V-Turbo | glm-5v-turbo | ✅ | ❌ | ✅ |
GLM-5-Turbo | glm-5-turbo | ✅ | ❌ | ✅ |
GLM-5 | glm-5 | ✅ | ❌ | ✅ |
Kimi-K2.6 | kimi-k2.6 | ✅ | ❌ | ✅ |
Kimi-K2.5 | kimi-k2.5 | ✅ | ❌ | ✅ |
MiniMax-M3 | minimax-m3 | ✅ | ✅ | ✅ |
MiniMax-M2.7 | minimax-m2.7 | ✅ | ✅ | ✅ |
MiniMax-M2.5 | minimax-m2.5 | ✅ | ✅ | ✅ |
Hy-MT2-Plus | hy-mt2-plus | ✅ | ❌ | ✅ |
https://tokenhub.tencentcloudmaas.com/v1https://tokenhub-intl.tencentcloudmaas.com/v1Parameter Name | Required | Type | Description |
model | Yes | String | Service ID. For platform-provided services, the service ID is the same as the model name.(for example, deepseek-v3.2). For the complete list, see the Supported Protocols by Model column in Model-Supported Protocol Overview.For user-created custom services, the service ID follows the format ep-xxxxxxxx and can be viewed on the online inference service page. |
messages | Yes | Array | |
stream | No | Boolean | Whether to enable streaming output. Valid values: true / false. The default value is false. |
stream_options | No | Object | Streaming output options. A common setting: {"include_usage": true} causes the last chunk to carry the usage statistics field (effective only when stream=true). |
temperature | No | Float | Sampling temperature, which controls output randomness. Valid values: [0.0, 2.0]. The default value is 1.0. A higher value results in more random output.Some models have specific value constraints. See the dedicated documentation for the corresponding model. |
top_p | No | Float | Probability threshold for Nucleus Sampling. Valid values: [0.0, 1.0]. The default value is 1.0. It is recommended to use it as an alternative to temperature. |
max_tokens | No | Integer | Limits the maximum number of output tokens per response. Reasoning tokens and response tokens of thinking models share this quota. It is recommended to increase it appropriately. |
n | No | Integer | The number of candidate responses generated for a single request. The default value is 1.Note: Billing is based on the total number of tokens when n > 1. |
stop | No | String or Array of String | Specifies the stop sequences for model output. When the generated result matches any of the specified sequences, the model stops outputting, and the response content does not include that stop sequence. It supports passing a single string or an array of strings, with a maximum of 4. For example, to have the model generate a list of 10 items and prevent it from continuing to write the 11th item, you can fill in this field with: ["11."]. |
seed | No | Integer | Random seed, used for result reproducibility. When the same seed value is used across multiple requests and other parameters remain consistent, the model is more likely to return identical or very similar results. |
frequency_penalty | No | Float | Frequency penalty. Valid values range from -2.0 to 2.0. The default value is 0. A positive value reduces the probability of tokens that have already appeared frequently being selected again, which can help mitigate repetitive content. |
presence_penalty | No | Float | Presence penalty. Valid values range from -2.0 to 2.0. The default value is 0. A positive value encourages the model to discuss new topics (based only on whether a Token has appeared, not on its frequency). |
logit_bias | No | Map | Modifies the probability of specific tokens appearing in the result. The key is the token ID, and the value is a bias within the range of -100 to 100. A value of -100 disables the token, and a value of 100 forces its use. |
logprobs | No | Boolean | Whether to return the log probabilities of output tokens. The default value is false. |
top_logprobs | No | Integer | Returns the N tokens with the highest probability at each position. Valid values range from 0 to 20. logprobs=true must be set concurrently. |
response_format | No | Object | Specifies the response output format. Common values: {"type": "text"}: Text output by default.{"type": "json_object"}: JSON mode, which forces the output of valid JSON.{"type": "json_schema", "json_schema": {...}}: Structured output, constrained by the specified Schema. |
tools | No | Array | A list of Function Calling tool definitions. Each tool contains a type: "function" and a function object (which includes name / description / parameters). |
tool_choice | No | String or Object | Tool invocation policy: "none": Tool calls are prohibited."auto": Automatically determines whether to call (default)."required": Forces the call of any tool.{"type": "function", "function": {"name": "xxx"}}: Forces the call of the specified tool. |
parallel_tool_calls | No | Boolean | Whether to allow multiple tools to be invoked in parallel within a single response. The default value is true. Setting it to false forces tools to be invoked serially, which facilitates debugging. |
thinking | No | Object | Controls the thinking mode. The default value varies across different models. For details, see Deep Thinking. Valid values: {"type": "enabled"} / {"type": "disabled"}. |
reasoning_effort | No | String | Controls the reasoning depth. It takes effect only on thinking models, and the default value varies across different models. For details, see Deep Thinking. Valid values: low / medium / high. |
user | No | String | A stable identifier for end users, facilitating auditing and troubleshooting. |
Field | Type | Description |
role | String | Role: system (system prompt), user (user), assistant (assistant), tool (tool response) |
content | String | Text content of the message. |
[system(optional) → user → assistant → user → ...], and must end with the user role.Parameter Name | Type | Description |
id | String | The unique identifier of the request. |
object | String | The object type, fixed as chat.completion. |
created | Integer | Creation time (Unix timestamp). |
model | String | The name of the model actually used. |
choices | Array | The list of candidate results returned by the model for a single request. For details, see choices array element. |
usage | Object | Token consumption statistics. |
Field | Type | Description |
index | Integer | Option index. |
message | Object | Response message containing role and content |
finish_reason | String | Reason for termination: stop (normal termination), length (maximum length reached), tool_calls (tool invocation required). |
Field | Type | Description |
prompt_tokens | Integer | Number of input tokens |
completion_tokens | Integer | Number of output tokens |
total_tokens | Integer | Total number of tokens (used for billing) |
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to try.curl -X POST 'https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions' \\-H 'Authorization: Bearer YOUR_API_KEY' \\-H 'Content-Type: application/json' \\-d '{"model": "deepseek-v3.2","messages": [{"role": "user", "content": "Hello, please introduce yourself"}]}'
from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",)response = client.chat.completions.create(model="deepseek-v3.2",messages=[{"role": "user", "content": "Hello, please introduce yourself"},],)print(response.choices[0].message.content)
import OpenAI from 'openai';const client = new OpenAI({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',});const response = await client.chat.completions.create({model: 'deepseek-v3.2',messages: [{ role: 'user', content: 'Hello, please introduce yourself' },],});console.log(response.choices[0].message.content);
// Using the OpenAI-compatible protocol, call the HTTP API directly with OkHttpimport okhttp3.*;import com.google.gson.Gson;import java.util.*;public class BasicChat {public static void main(String[] args) throws Exception {Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("messages", Arrays.asList(Map.of("role", "user", "content", "Hello, please introduce yourself")));RequestBody requestBody = RequestBody.create(new Gson().toJson(body),MediaType.parse("application/json"));Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions").header("Authorization", "Bearer YOUR_API_KEY").post(requestBody).build();try (Response response = new OkHttpClient().newCall(request).execute()) {System.out.println(response.body().string());}}}
package mainimport ("bytes""encoding/json""fmt""io""net/http")func main() {body := map[string]interface{}{"model": "deepseek-v3.2","messages": []map[string]string{{"role": "user", "content": "Hello, please introduce yourself"},},}payload, _ := json.Marshal(body)req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",bytes.NewBuffer(payload))req.Header.Set("Authorization", "Bearer YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, err := http.DefaultClient.Do(req)if err != nil {panic(err)}defer resp.Body.Close()data, _ := io.ReadAll(resp.Body)fmt.Println(string(data))}
{"id": "5e9c7ae9-e0e4-4ec1-bbd0-22bcfda61e45","object": "chat.completion","model": "deepseek-v3.2","choices": [{"index": 0,"message": {"role": "assistant","content": "Hello! Nice to meet you! 😊\\n\\nI am DeepSeek, an AI assistant created by DeepSeek Company. Let me briefly introduce myself:\\n\\n**My Features:**\\n- 📚 My knowledge is up to date as of July 2024, and I am the latest version of the DeepSeek model.\\n- 💬 I am a pure text conversation model, focused on understanding and generating textual content.\\n- 📁 I support file uploads—I can process images, txt, pdf, ppt, word, excel, and other files, and read text information from them.\\n- 🌐 I support web search (you need to manually enable it in the Web/App).\\n- 💾 I have a 128K context length, allowing me to remember our longer conversations.\\n\\n**What I can do for you:**\\n- Answer various questions and engage in in-depth discussions.\\n- Assist with writing, translation, and analysis.\\n- Process uploaded document content.\\n- Provide suggestions for learning, work, and life.\\n\\n**Important Notes:**\\n- I am completely free to use, with no paid plans.\\n- I currently do not support voice features.\\n- You can download the App from official app stores.\\n\\nMy response style is warm and detailed, and I hope to provide you with a pleasant communication experience! If you have anything to talk about or need help with, just let me know! ✨"},"finish_reason": "stop"}],"usage": {"prompt_tokens": 10,"completion_tokens": 244,"total_tokens": 254,"prompt_tokens_details": {"cached_tokens": 0},"completion_tokens_details": {"reasoning_tokens": 0}}}
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to try.curl -X POST 'https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions' \\-H 'Authorization: Bearer YOUR_API_KEY' \\-H 'Content-Type: application/json' \\-d '{"model": "deepseek-v3.2","messages": [{"role": "system", "content": "You are a helpful AI assistant."},{"role": "user", "content": "Calculate 1+1"}],"stream": true}'
from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",)stream = client.chat.completions.create(model="deepseek-v3.2",messages=[{"role": "system", "content": "You are a helpful AI assistant."},{"role": "user", "content": "Calculate 1+1"},],stream=True,)for chunk in stream:if chunk.choices and chunk.choices[0].delta.content:print(chunk.choices[0].delta.content, end="", flush=True)
import OpenAI from 'openai';const client = new OpenAI({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',});const stream = await client.chat.completions.create({model: 'deepseek-v3.2',messages: [{ role: 'system', content: 'You are a helpful AI assistant.' },{ role: 'user', content: 'Calculate 1+1' },],stream: true,});for await (const chunk of stream) {process.stdout.write(chunk.choices[0]?.delta?.content || '');}
// For streaming calls based on SSE, use OkHttp to receive line-by-line responses.import okhttp3.*;import okhttp3.sse.*;import com.google.gson.Gson;import java.util.*;public class Streaming {public static void main(String[] args) {Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("messages", Arrays.asList(Map.of("role", "system", "content", "You are a helpful AI assistant."),Map.of("role", "user", "content", "Calculate 1+1")));body.put("stream", true);Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions").header("Authorization", "Bearer YOUR_API_KEY").post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json"))).build();EventSources.createFactory(new OkHttpClient()).newEventSource(request,new EventSourceListener() {@Override public void onEvent(EventSource es, String id, String type, String data) {if (!"[DONE]".equals(data)) System.out.print(data);}});}}
package mainimport ("bufio""bytes""encoding/json""fmt""net/http""strings")func main() {body, _ := json.Marshal(map[string]interface{}{"model": "deepseek-v3.2","messages": []map[string]string{{"role": "system", "content": "You are a helpful AI assistant."},{"role": "user", "content": "Calculate 1+1"},},"stream": true,})req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",bytes.NewBuffer(body))req.Header.Set("Authorization", "Bearer YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, _ := http.DefaultClient.Do(req)defer resp.Body.Close()scanner := bufio.NewScanner(resp.Body)for scanner.Scan() {line := scanner.Text()if strings.HasPrefix(line, "data: ") && line != "data: [DONE]" {fmt.Println(strings.TrimPrefix(line, "data: "))}}}
data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{"role":"assistant","content":"1"},"finish_reason":null}]}data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{"content":"+"},"finish_reason":null}]}data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{"content":"1"},"finish_reason":null}]}data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{"content":"="},"finish_reason":null}]}data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{"content":"2"},"finish_reason":null}]}data: {"id":"chatcmpl-abc123","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}data: [DONE]
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to try.curl -X POST 'https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions' \\-H 'Authorization: Bearer YOUR_API_KEY' \\-H 'Content-Type: application/json' \\-d '{"model": "deepseek-v3.2","messages": [{"role": "system", "content": "You are a professional English translation assistant. Translate user-input Chinese into English, and translate English into Chinese. Return only the translation result, without any explanation."},{"role": "user", "content": "The weather is really nice today."}]}'
from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",)response = client.chat.completions.create(model="deepseek-v3.2",messages=[{"role": "system", "content": "You are a professional English translation assistant. Translate user-input Chinese into English, and translate English into Chinese. Return only the translation result, without any explanation."},{"role": "user", "content": "The weather is really nice today."}],)print(response.choices[0].message.content)
import OpenAI from 'openai';const client = new OpenAI({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',});const response = await client.chat.completions.create({model: 'deepseek-v3.2',messages: [{ role: 'system', content: 'You are a professional English translation assistant. Translate user-input Chinese into English, and translate English into Chinese. Return only the translation result, without any explanation.' },{ role: 'user', content: 'The weather is really nice today.' },],});console.log(response.choices[0].message.content);
import okhttp3.*;import com.google.gson.Gson;import java.util.*;public class SystemPrompt {public static void main(String[] args) throws Exception {Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("messages", Arrays.asList(Map.of("role", "system", "content", "You are a professional English translation assistant. Translate user-input Chinese into English, and translate English into Chinese. Return only the translation result, without any explanation."),Map.of("role", "user", "content", "The weather is really nice today.")));Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions").header("Authorization", "Bearer YOUR_API_KEY").post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json"))).build();try (Response response = new OkHttpClient().newCall(request).execute()) {System.out.println(response.body().string());}}}
package mainimport ("bytes""encoding/json""fmt""io""net/http")func main() {body, _ := json.Marshal(map[string]interface{}{"model": "deepseek-v3.2","messages": []map[string]string{{"role": "system", "content": "You are a professional English translation assistant. Translate user-input Chinese into English, and translate English into Chinese. Return only the translation result, without any explanation."},{"role": "user", "content": "The weather is really nice today."}},})req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",bytes.NewBuffer(body))req.Header.Set("Authorization", "Bearer YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, _ := http.DefaultClient.Do(req)defer resp.Body.Close()data, _ := io.ReadAll(resp.Body)fmt.Println(string(data))}
{"id": "5d42fea3-413e-42ce-99b2-0d1595dae996","object": "chat.completion","model": "deepseek-v3.2","choices": [{"index": 0,"message": {"role": "assistant","content": "The weather is really nice today."},"finish_reason": "stop"}],"usage": {"prompt_tokens": 38,"completion_tokens": 7,"total_tokens": 45,"prompt_tokens_details": {"cached_tokens": 0},"completion_tokens_details": {"reasoning_tokens": 0}}}
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to try.curl -X POST 'https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions' \\-H 'Authorization: Bearer YOUR_API_KEY' \\-H 'Content-Type: application/json' \\-d '{"model": "deepseek-v3.2","messages": [{"role": "user", "content": "Please introduce quantum computing."}{"role": "assistant", "content": "Quantum computing is a computational approach that leverages the principles of quantum mechanics for information processing..."},{"role": "user", "content": "What are the differences between it and traditional computing?"}]}'
from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",)response = client.chat.completions.create(model="deepseek-v3.2",messages=[{"role": "user", "content": "Please introduce quantum computing."}{"role": "assistant", "content": "Quantum computing is a computational approach that leverages the principles of quantum mechanics for information processing..."},{"role": "user", "content": "What are the differences between it and traditional computing?"}],)print(response.choices[0].message.content)
import OpenAI from 'openai';const client = new OpenAI({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',});const response = await client.chat.completions.create({model: 'deepseek-v3.2',messages: [{"role": "user", "content": "Please introduce quantum computing."}{"role": "assistant", "content": "Quantum computing is a computational approach that leverages the principles of quantum mechanics for information processing..."},{"role": "user", "content": "What are the differences between it and traditional computing?"}],});console.log(response.choices[0].message.content);
import okhttp3.*;import com.google.gson.Gson;import java.util.*;public class MultiTurn {public static void main(String[] args) throws Exception {Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("messages", Arrays.asList(Map.of("role", "user", "content", "Please introduce quantum computing."),Map.of("role", "assistant", "content", "Quantum computing is a computational approach that leverages the principles of quantum mechanics for information processing..."),Map.of("role", "user", "content", "What are the differences between it and traditional computing?")));Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions").header("Authorization", "Bearer YOUR_API_KEY").post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json"))).build();try (Response response = new OkHttpClient().newCall(request).execute()) {System.out.println(response.body().string());}}}
package mainimport ("bytes""encoding/json""fmt""io""net/http")func main() {body, _ := json.Marshal(map[string]interface{}{"model": "deepseek-v3.2","messages": []map[string]string{{"role": "user", "content": "Please introduce quantum computing."}{"role": "assistant", "content": "Quantum computing is a computational approach that leverages the principles of quantum mechanics for information processing..."},{"role": "user", "content": "What are the differences between it and traditional computing?"}},})req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",bytes.NewBuffer(body))req.Header.Set("Authorization", "Bearer YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, _ := http.DefaultClient.Do(req)defer resp.Body.Close()data, _ := io.ReadAll(resp.Body)fmt.Println(string(data))}
{"id": "fda59c08-6a85-4514-bdbf-d77a8d68e018","object": "chat.completion","model": "deepseek-v3.2","choices": [{"index": 0,"message": {"role": "assistant","content": "Good, this is a very core question. The fundamental difference between quantum computing and traditional computing lies in their basic units of information processing and their working principles.\\n\\nWe can start with a classic analogy:\\n\\n* **A traditional computer** is like a **librarian** (CPU) running down a long corridor (bus) in a vast **library**. The librarian can only open one room (memory address) at a time, check one book (one bit of data), and then make a decision.\\n* **A quantum computer**, on the other hand, is like having **all librarians** (qubits) **enter all rooms** simultaneously and read **every possible combination of all books** in an instant, then tell you the final result.\\n\\nBelow, we provide a detailed comparison from several key dimensions:\\n\\n### 1. Basic Information Unit: Bit vs. Qubit\\n\\n| Feature | Traditional Computing (Bit) | Quantum Computing (Qubit) |\\n| :--- | :--- | :--- |\\n| **State** | **Binary**: Can only be **0** or **1**. Like a light switch, it's either on or off. Very definite. | **Superposition**: Can be **both** 0 and 1 simultaneously, or any probabilistic combination of 0 and 1. Like a \\"quantum light\\" that is both on and off at the same time. |\\n| **Representation** | A definite, discrete value. | A state vector, represented in Dirac notation as: \\\\|ψ⟩ = α\\\\|0⟩ + β\\\\|1⟩, where α and β are complex numbers, and \\\\|α\\\\|² + \\\\|β\\\\|² = 1. |\\n| **Core Difference** | **Deterministic**: Each bit has a definite value at any given moment. | **Probabilistic**: When a qubit is measured, it collapses to 0 with probability \\\\|α\\\\|² and to 1 with probability \\\\|β\\\\|². |\\n\\n### 2. Working Principle: Logic Gates vs. Quantum Properties\\n\\n| Feature | Traditional Computing | Quantum Computing |\\n| :--- | :--- | :--- |\\n| **Operation Method** | Uses **logic gates** (e.g., AND, OR, NOT) to operate on bits. An operation changes the state of one or a group of bits. | Uses **quantum logic gates** to operate on qubits. These operations are **reversible** and can leverage superposition for **parallel computation**. |\\n| **Core Advantage** | **Serial Processing**: Tasks are broken down into a series of steps executed sequentially. Highly efficient for simple, logically clear tasks. | **Quantum Parallelism**: Because qubits are in superposition, a single quantum operation can **act on all possible inputs simultaneously**. This is the source of quantum speedup. |\\n| **Unique Phenomenon** | None | **Quantum Entanglement**: Two or more qubits can form a mysterious correlation. Regardless of distance, measuring one qubit instantly determines the state of the other(s). This allows a quantum computer to tightly link the states of different qubits for highly collaborative computation. |\\n\\n### 3. Performance and Applicable Domains\\n\\n| Feature | Traditional Computing | Quantum Computing |\\n| :--- | :--- | :--- |\\n| **Strong Suit** | - **General-purpose computing**: Office software, web browsing, games<br>- **Logic control**: Operating systems, application logic<br>- **Most data processing**: DMC, spreadsheets | - **Exponential speedup in specific domains**:<br> - **Cryptography**: Breaking encryption algorithms like RSA (Shor's algorithm)<br> - **Material simulation**: Precisely simulating the quantum properties of molecules and materials<br> - **Optimization problems**: Logistics route planning, financial portfolio optimization<br> - **Artificial intelligence**: Accelerating machine learning training |\\n| **Computational Complexity** | For certain complex problems (e.g., large number factorization), traditional algorithms require **exponentially** increasing time. | For specific problems, quantum algorithms can reduce complexity to the **polynomial** level, achieving \\"quantum supremacy.\\" |\\n| **Output Result** | Precise, deterministic results. | Typically **probabilistic** results. Because measurement is required, we obtain a potentially correct answer, so algorithms often need to run multiple times to increase confidence. |\\n\\n### 4. Physical Implementation and Challenges\\n\\n| Feature | Traditional Computer | Quantum Computer |\\n| :--- | :--- | :--- |\\n| **Hardware Foundation** | Based on **transistors** (semiconductors), mature technology, allowing for large-scale integration (e.g., CPUs with billions of transistors). | Requires physical systems that can maintain quantum states, such as superconducting circuits, ion traps, photonic qubits. Technology is still in its early stages. |\\n| **Main Challenge** | Power consumption, heat dissipation, transistor size approaching physical limits (Moore's Law slowing). | **Quantum Decoherence**: Quantum states are extremely fragile and easily lose their quantum properties due to environmental interference (e.g., heat, vibration). Requires extremely low temperatures (near absolute zero) and highly isolated environments. |\\n| **Error Correction** | Very low error rates, relatively simple error correction (e.g., parity check). | High error rates, requiring complex **quantum error-correcting codes** that use multiple physical qubits to encode one logical qubit, incurring significant overhead. |\\n\\n### Summary Table\\n\\n| Comparison Dimension | Traditional Computing | Quantum Computing |\\n| :--- | :--- | :--- |\\n| **Basic Unit** | Bit (0 or 1) | Qubit (Superposition: Superposition of 0 and 1) |\\n| **Operation Method** | Logic gates (serial) | Quantum gates (parallel) |\\n| **Core Principle** | Boolean logic | Superposition, entanglement, interference |\\n| **Result Output** | Deterministic | Probabilistic |\\n| **Strong Suit** | General tasks, logic control | Specific complex problems (e.g., simulation, optimization, cryptanalysis) |\\n| **Technology Maturity** | Very mature, widely used | Early stage, primarily used for research and specific computations |\\n| **Relationship with Users** | **Complementary Relationship**: Quantum computers are **not** intended to replace your phone or laptop. They function more like a **specialized accelerator** for solving specific, intractable problems that traditional computers cannot solve in the foreseeable future. In the future, we might access quantum computers via the cloud to handle the most complex parts, while traditional computers handle daily tasks and user interaction. |\\n\\nIn simple terms, a traditional computer is a \\"precise sharpshooter,\\" while a quantum computer is a \\"prophet capable of exploring all possibilities simultaneously.\\" Each has its strengths, and they will work together for a long time to come."},"finish_reason": "stop"}],"usage": {"prompt_tokens": 32,"completion_tokens": 1321,"total_tokens": 1353,"prompt_tokens_details": {"cached_tokens": 0},"completion_tokens_details": {"reasoning_tokens": 0}}}
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to experience. For tool calls in thinking mode, you must provide the historical reasoning_content in each request round to obtain the best results. For details, see Interleaved Thinking.curl -X POST 'https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions' \\-H 'Authorization: Bearer YOUR_API_KEY' \\-H 'Content-Type: application/json' \\-d '{"model": "deepseek-v3.2","messages": [{"role": "user", "content": "What is the weather like in Beijing today?"}],"tools": [{"type": "function","function": {"name": "get_weather","description": "Obtain weather information for a specified city","parameters": {"type": "object","properties": {"city": {"type": "string", "description": "City name, such as: Beijing"}},"required": ["city"]}}}],"tool_choice": "auto"}'
from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",)tools = [{"type": "function","function": {"name": "get_weather","description": "Obtain weather information for a specified city","parameters": {"type": "object","properties": {"city": {"type": "string", "description": "City name, such as: Beijing"}},"required": ["city"],},},}]response = client.chat.completions.create(model="deepseek-v3.2",messages = [{"role": "user", "content": "What is the weather like in Beijing today?"}],tools=tools,tool_choice="auto",)print(response.choices[0].message)
import OpenAI from 'openai';const client = new OpenAI({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',});const tools = [{type: 'function',function: {name: 'get_weather',"description": "Obtain weather information for a specified city",parameters: {type: 'object',"properties": {"city": {"type": "string", "description": "City name, such as: Beijing"}},required: ['city'],},},}];const response = await client.chat.completions.create({model: 'deepseek-v3.2',messages: [{ role: 'user', content: 'What is the weather like in Beijing today?' }],tools,tool_choice: 'auto',});console.log(response.choices[0].message);
import okhttp3.*;import com.google.gson.Gson;import java.util.*;public class FunctionCalling {public static void main(String[] args) throws Exception {Map<String, Object> tool = Map.of("type", "function","function", Map.of("name", "get_weather","description", "Obtain weather information for a specified city","parameters", Map.of("type", "object","properties", Map.of("city", Map.of("type", "string", "description", "City name, such as: Beijing")),"required", List.of("city"))));Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("messages", List.of(Map.of("role", "user", "content", "What is the weather like in Beijing today?")));body.put("tools", List.of(tool));body.put("tool_choice", "auto");Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions").header("Authorization", "Bearer YOUR_API_KEY").post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json"))).build();try (Response response = new OkHttpClient().newCall(request).execute()) {System.out.println(response.body().string());}}}
package mainimport ("bytes""encoding/json""fmt""io""net/http")func main() {tool := map[string]interface{}{"type": "function","function": map[string]interface{}{"name": "get_weather","description": "Obtain weather information for a specified city","parameters": map[string]interface{}{"type": "object","properties": map[string]interface{}{"city": map[string]interface{}{"type": "string", "description": "City name, such as: Beijing"},},"required": []string{"city"},},},}body, _ := json.Marshal(map[string]interface{}{"model": "deepseek-v3.2","messages": []map[string]string{{"role": "user", "content": "What is the weather like in Beijing today?"}},"tools": []map[string]interface{}{tool},"tool_choice": "auto",})req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",bytes.NewBuffer(body))req.Header.Set("Authorization", "Bearer YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, _ := http.DefaultClient.Do(req)defer resp.Body.Close()data, _ := io.ReadAll(resp.Body)fmt.Println(string(data))}
{"choices": [{"message": {"role": "assistant","content": null,"tool_calls": [{"id": "call_abc123","type": "function","function": {"name": "get_weather","arguments": "{\\"city\\": \\"Beijing\\"}"}}]},"finish_reason": "tool_calls"}]}
{"model": "deepseek-v3.2","messages": [{"role": "user", "content": "What is the weather like in Beijing today?"},{"role": "assistant", "content": null, "tool_calls": [{"id": "call_abc123", "type": "function", "function": {"name": "get_weather", "arguments": "{\\"city\\": \\"Beijing\\"}"}}]},{"role": "tool", "tool_call_id": "call_abc123", "content": "{\\"temperature\\": 22, \\"weather\\": \\"Sunny\\", \\"humidity\\": 45}"}]}
https://tokenhub.tencentcloudmaas.comhttps://tokenhub-intl.tencentcloudmaas.comField | Support Status | Description |
anthropic-beta | Ignored. | Ignore the header. |
anthropic-version | Ignored. | Ignore the header. |
x-api-key | Fully supported | Used for authentication |
Field | Support Status | Description |
model | Supported | |
max_tokens | Fully supported | Maximum number of output tokens |
container | Ignored. | Ignore this field |
mcp_servers | Ignored. | Ignore this field |
metadata | Ignored. | Ignore this field |
service_tier | Ignored. | Ignore this field |
stop_sequences | Fully supported | Stop sequences |
stream | Fully supported | Streaming response |
system | Fully supported | System message |
temperature | Fully supported | Temperature parameter (0.0-2.0) |
thinking | Ignored. | Ignore this field |
top_k | Ignored. | Ignore this field |
top_p | Fully supported | Top-p sampling |
Field | Support Status | Description |
name | Fully supported | Tool Name |
input_schema | Fully supported | Input parameter schema |
description | Fully supported | Tool description |
cache_control | Ignored. | Ignore this field |
tool_choice | String format | Fully supported |
tool_choice | Object format | Fully supported |
tool_choice.disable_parallel_tool_use | Ignored. | Ignore this field |
Field | Support Status |
none | Fully supported |
auto | Fully supported |
any | Fully supported |
tool | Fully supported |
disable_parallel_tool_use | Ignored. |
Field Type | Variant | Subfield | Support Status |
content | string | - | Fully supported |
content | array, type="text" | text | Fully supported |
content | array, type="text" | cache_control | Ignored. |
content | array, type="text" | citations | Ignored. |
content | array, type="image" | - | Supported by some models. For details, refer to the invocation guide for each model. |
content | array, type="document" | - | Not supported. |
content | array, type="search_result" | - | Not supported. |
content | array, type="thinking" | - | Ignored. |
content | array, type="redacted_thinking" | - | Not supported. |
content | array, type="tool_use" | id | Fully supported |
content | array, type="tool_use" | input | Fully supported |
content | array, type="tool_use" | name | Fully supported |
content | array, type="tool_use" | cache_control | Ignored. |
content | array, type="tool_result" | tool_use_id | Fully supported |
content | array, type="tool_result" | content | Fully supported |
content | array, type="tool_result" | cache_control | Ignored. |
content | array, type="tool_result" | is_error | Ignored. |
YOUR_API_KEY with the API Key you created, and replace model with the service ID you want to try.curl https://tokenhub-intl.tencentcloudmaas.com/v1/messages \\-H "Content-Type: application/json" \\-H "x-api-key: YOUR_API_KEY" \\-d '{"model": "deepseek-v3.2","max_tokens": 1000,"stream": true,"system": [{"type": "text", "text": "You are a helpful assistant."}],"messages": [{"role": "user", "content": [{"type": "text", "text": "Hi, how are you?"}]}]}'
import anthropicclient = anthropic.Anthropic(api_key="YOUR_API_KEY",base_url="https://tokenhub-intl.tencentcloudmaas.com",)with client.messages.stream(model="deepseek-v3.2",max_tokens=1000,system="You are a helpful assistant.",messages=[{"role": "user", "content": "Hi, how are you?"}],) as stream:for text in stream.text_stream:print(text, end="", flush=True)
import Anthropic from '@anthropic-ai/sdk';const client = new Anthropic({apiKey: 'YOUR_API_KEY',baseURL: 'https://tokenhub-intl.tencentcloudmaas.com',});const stream = await client.messages.stream({model: 'deepseek-v3.2',max_tokens: 1000,system: 'You are a helpful assistant.',messages: [{ role: 'user', content: 'Hi, how are you?' }],});for await (const event of stream) {if (event.type === 'content_block_delta' && event.delta.type === 'text_delta') {process.stdout.write(event.delta.text);}}
import okhttp3.*;import okhttp3.sse.*;import com.google.gson.Gson;import java.util.*;public class AnthropicCall {public static void main(String[] args) {Map<String, Object> body = new HashMap<>();body.put("model", "deepseek-v3.2");body.put("max_tokens", 1000);body.put("stream", true);body.put("system", List.of(Map.of("type", "text", "text", "You are a helpful assistant.")));body.put("messages", List.of(Map.of("role", "user","content", List.of(Map.of("type", "text", "text", "Hi, how are you?")))));Request request = new Request.Builder().url("https://tokenhub-intl.tencentcloudmaas.com/v1/messages").header("x-api-key", "YOUR_API_KEY").header("Content-Type", "application/json").post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json"))).build();EventSources.createFactory(new OkHttpClient()).newEventSource(request,new EventSourceListener() {@Override public void onEvent(EventSource es, String id, String type, String data) {System.out.println(data);}});}}
package mainimport ("bufio""bytes""encoding/json""fmt""net/http""strings")func main() {body, _ := json.Marshal(map[string]interface{}{"model": "deepseek-v3.2","max_tokens": 1000,"stream": true,"system": []map[string]string{{"type": "text", "text": "You are a helpful assistant."},},"messages": []map[string]interface{}{{"role": "user","content": []map[string]string{{"type": "text", "text": "Hi, how are you?"},},},},})req, _ := http.NewRequest("POST","https://tokenhub-intl.tencentcloudmaas.com/v1/messages",bytes.NewBuffer(body))req.Header.Set("x-api-key", "YOUR_API_KEY")req.Header.Set("Content-Type", "application/json")resp, _ := http.DefaultClient.Do(req)defer resp.Body.Close()scanner := bufio.NewScanner(resp.Body)for scanner.Scan() {line := scanner.Text()if strings.HasPrefix(line, "data: ") {fmt.Println(strings.TrimPrefix(line, "data: "))}}}
data: {"content_block":{"text":"","type":"text"},"index":1,"type":"content_block_start"}event: content_block_deltadata: {"delta":{"text":"Hey","type":"text_delta"},"index":0,"type":"content_block_delta"}event: content_block_deltadata: {"delta":{"text":"! I'm doing well, thanks for asking! I'm","type":"text_delta"},"index":0,"type":"content_block_delta"}event: content_block_deltadata: {"delta":{"text":" here and ready to help with whatever you need.","type":"text_delta"},"index":0,"type":"content_block_delta"}event: content_block_deltadata: {"delta":{"text":" How are you doing today? Is there something I","type":"text_delta"},"index":0,"type":"content_block_delta"}event: content_block_deltadata: {"delta":{"text":" can assist you with?","type":"text_delta"},"index":0,"type":"content_block_delta"}event: content_block_stopdata: {"index":1,"type":"content_block_stop"}event: message_deltadata: {"delta":{"stop_reason":"end_turn","stop_sequence":null},"type":"message_delta","usage":{"output_tokens":57}}event: message_stopdata: {"type":"message_stop"}
npm install -g @anthropic-ai/claude-code
export ANTHROPIC_BASE_URL=https://tokenhub-intl.tencentcloudmaas.comexport ANTHROPIC_AUTH_TOKEN=${API_KEY}export API_TIMEOUT_MS=600000export ANTHROPIC_MODEL=${MODEL_NAME}export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1
cd my-projectclaude
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