DeepSeek V4.1 Flash vs GPT-5.6 Sol: price, benchmarks and how to switch
DeepSeek V4.1 Flash 1017 on Inferway next to OpenAI's GPT-5.6 Sol and GPT-6.1 Sol. Prices come from each side's public price list and every benchmark score names its source. Inferway does not offer GPT models; this page only helps you decide whether a different model is worth a trial.
OpenAI, GPT, Anthropic, Claude and the other model and company names on this page belong to their owners. They are used here only to say what is being compared. Inferway is not affiliated with them, does not resell their models, and this page is not an endorsement by or from them.
Price (per million tokens, USD)
| Item | Inferway DeepSeek V4.1 Flash 1017 | OpenAI GPT-5.6 Sol | OpenAI GPT-6.1 Sol |
|---|---|---|---|
| Input | $0.07 | $4.00 | $2.00 |
| Cached input | $0.003 | $0.40 | $0.10 |
| Output | $0.15 | $20.00 | $10.00 |
Against OpenAI GPT-5.6 Sol: input about 98% lower, output about 99% lower (list prices, rounded down).
Against OpenAI GPT-6.1 Sol: input about 96% lower, output about 98% lower (list prices, rounded down).
Inferway price in CNY (China market): ¥0.50 input, ¥1.10 output per million tokens.
Both sides are in USD so the rows compare like for like. Inferway list price from the live public catalog; the other side's price from its own public price page, read on the date shown under Sources.
Cached-input rows put list prices side by side; the caching mechanisms are different features, not equivalents.
No first-token latency row: Inferway has no published measurement for this comparison yet.
Context window and output limit
| Item | Inferway DeepSeek V4.1 Flash 1017 | OpenAI GPT-5.6 Sol |
|---|---|---|
| Context window | 1M | Not listed by the source (to be filled in) |
| Max output | 256K | Not listed by the source (to be filled in) |
Benchmark scores: DeepSeek's release table
All eleven rows of DeepSeek's release table where GPT-5.6 Sol has a score are listed, including the two where DeepSeek V4.1 Flash 1017 is behind (HLE and ZeroBench-main). GPT-6.1 Sol has no score in any source we use, so it is not in this table.
| Benchmark | DeepSeek V4.1 Flash 1017 | GPT-5.6 Sol |
|---|---|---|
| HLE, no tools | 42.6 (44.0†) | 44.5 |
| Terminal-Bench 4.0 | 42.3 | 39.9 |
| DeepSWE v1.1 | 77.0 | 73.0 |
| ProgramBench | 29.1 | 23.0 |
| NL2Repo-Bench | 68.2 | 56.8 |
| Automation-Bench v1.0.6 | 60.5 | 45.8 |
| Agents' Last Exam | 35.4 | 26.7 |
| Apex Bench v1.1 | 72.1 | 54.3 |
| Chartography, with tools | 83.0 | 79.9 |
| BabyVision, with tools | 92.5 | 88.9 |
| ZeroBench-main, with tools, pass@5 | 51.0 | 53.0 |
The higher score in each row is shaded. Harnesses differ between rows (Terminal-Bench uses the Claude Code harness, DeepSWE the Mini-SWE-V2 harness), so compare within a row, not across rows. † marks the HLE text-only subset.
Data handling
An external organization processes request content. Inferway's zero data retention commitment does not apply. See the Privacy Policy for data handling details.
If data retention is your main concern, the catalog also lists DeepSeek V4.1 Flash 1017 ZDR, which sends requests only to provider endpoints that state they do not keep prompts or responses. That statement is the provider's own and Inferway has not verified it, and the model is still outside Inferway's own zero data retention commitment.
DeepSeek V4.1 Flash 1017 ZDR →Zero data retention: boundaries and comparison →
Choosing between them
Worth a small trial when
- Your traffic is mostly chat completions with streaming and function calling, and cost is the main pressure.
- You can run the same prompts through both models on your own evaluation set before moving any traffic.
Stay with the official API when
- You depend on embeddings, the legacy /v1/completions endpoint or the Responses API, none of which Inferway serves today.
- You need a model that is not in the Inferway catalog, such as GPT-6.1 Sol.
Check on your own data first when
- Your tasks look like HLE-style knowledge questions or ZeroBench-style visual puzzles: DeepSeek's own table has DeepSeek V4.1 Flash 1017 below GPT-5.6 Sol on both.
Differences from calling the official API
- Supported on /v1/chat/completions: model, messages (system, user, assistant and tool roles, text and image blocks), stream, temperature, top_p, max_tokens, stop, tools and tool_choice, response_format and stream_options. Not served: legacy /v1/completions and embeddings.
- A non-streaming request is held to 4,096 output tokens in total (max_tokens × n); set stream: true for longer output.
- The Responses endpoint (/v1/responses) is not open yet.
How to switch
OpenAI Python SDK
With the standard openai SDK only base_url, the API key and the model id change.
import os from openai import OpenAI client = OpenAI( base_url="https://api.inferway.ai/v1", api_key=os.environ["INFERWAY_API_KEY"], ) stream = client.chat.completions.create( model="deepseek/deepseek-v4.1-flash-1017", messages=[{"role": "user", "content": "Hello!"}], stream=True, ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True)
Setup recipes are not proof that a client works with a model. Each client guide marks what has been tested, and what has not stays marked unverified.
Migrating from the OpenAI API →Client guides →Model page: DeepSeek V4.1 Flash 1017 →
Sources
Every number about another company's model on this page comes from one of these pages. Scores are vendor-published and have not been reproduced by Inferway.
- developers.openai.com/api/docs/pricing · read on 2026-11-01
- huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 · read on 2026-11-01