import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "deepseek/deepseek-chat-v3.1", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "deepseek/deepseek-chat-v3.1", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"deepseek/deepseek-chat-v3.1","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| SWE-bench Verified | 66.0% | Resolving verified real GitHub issues | Source | July 12, 2026 |
| LiveCodeBench | 56.4% | Contamination-free competitive programming problems | Source | July 12, 2026 |
| GPQA Diamond | 74.9% | Google-proof graduate science questions (hardest subset) | Source | July 12, 2026 |
| AIME 2025 | 49.8% | Competition mathematics (AIME), 2025 | Source | July 12, 2026 |
| Intelligence | 13.7 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Math | 49.7 | Composite score across standardised mathematics evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
DeepSeek-V3.1 This page | Coding + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
DeepSeek-V3.1 has a 128,000 tokens context window and can return up to 8,000 tokens.
DeepSeek-V3.1 takes text as input and returns text.
Use deepseek/deepseek-chat-v3.1 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
DeepSeek-V3.1 became available on August 28, 2025.
DeepSeek-V3.1 is priced at input $0.89401 / 1M tokens, output $2.33818 / 1M tokens, cached input $0.75647 / 1M tokens.
Yes, DeepSeek-V3.1 can stream responses as they are generated.
DeepSeek-V3.1 was built by DeepSeek.
Yes, its capabilities include reasoning alongside function calling and structured outputs.