Mistral Large 3 vs Step 3.5 Flash vs GPT-5.1 Codex mini
Step 3.5 Flash comes out ahead, 62 to 59 and 50 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
- Our pick
StepFunStep 3.5 Flash
62/100- ECI—
- Price$0.10 / $0.30
- Context256K
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Step 3.5 Flash is our pick
Step 3.5 Flash is the better all-round choice, scoring 62/100 against GPT-5.1 Codex mini (59) and Mistral Large 3 (50). It leads on price. GPT-5.1 Codex mini wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceStep 3.5 FlashStep 3.5 Flash $0.15 · GPT-5.1 Codex mini $0.688 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Large 3 262,144 · Step 3.5 Flash 256,000 tokens
- Widest inputsMistral Large 3 and GPT-5.1 Codex miniMistral Large 3: Text, Images · Step 3.5 Flash: Text · GPT-5.1 Codex mini: Text, Images
- Self-hostingMistral Large 3 and Step 3.5 FlashPublishes downloadable weights
| Measure | Weight | Mistral Large 3 | Step 3.5 Flash | GPT-5.1 Codex mini |
|---|---|---|---|---|
| Price | 50% | 56 | 89 | 58 |
| Inputs & features | 30% | 50 | 35 | 70 |
| Context window | 20% | 37 | 36 | 44 |
| Overall | 100% | 50/100 | 62/100 | 59/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Large 3Mistral AI | Step 3.5 FlashStepFun | GPT-5.1 Codex miniOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.10 (best) | $0.25 |
| Output | $1.50 | $0.30 (best) | $2.00 |
| Cached input | $0.05 | $0.02 (best) | — |
| Blended (3:1) | $0.75 | $0.15 (best) | $0.688 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official StepFun (Global) API | Median of 10 providers |
| Limits | |||
| Context window | 262,144 tokens | 256,000 tokens | 400,000 tokens (best) |
| Max output | 262,144 tokens (best) | 256,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yeslow · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | mistral-large-2512 | step-3.5-flash | — |
| API providers | 13 (best) | 8 | 10 |
| Released | Dec 2, 2025 | Jan 29, 2026 | Nov 13, 2025 |
| Knowledge cutoff | Nov 2024 | Jan 2025 | Sep 30, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Large 3$8.00
- Step 3.5 Flash$1.60
- GPT-5.1 Codex mini$6.50
Which should you choose?
Which is better: Mistral Large 3, Step 3.5 Flash or GPT-5.1 Codex mini?
Step 3.5 Flash is the better all-round choice, scoring 62/100 against GPT-5.1 Codex mini (59) and Mistral Large 3 (50). It leads on price. GPT-5.1 Codex mini wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Mistral Large 3, Step 3.5 Flash or GPT-5.1 Codex mini?
Step 3.5 Flash is cheaper at $0.10 input / $0.30 output per million tokens (official StepFun (Global) API price). GPT-5.1 Codex mini costs $0.25 input / $2.00 output per million tokens (median across 10 API providers); Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Step 3.5 Flash versus $0.688 for GPT-5.1 Codex mini (4.6× as much) and $0.75 for Mistral Large 3 (5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Large 3 has not been scored yet, Step 3.5 Flash has not been scored yet and GPT-5.1 Codex mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 3, Step 3.5 Flash and GPT-5.1 Codex mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.1 Codex mini has the largest context window at 400,000 tokens, against 262,144 for Mistral Large 3 and 256,000 for Step 3.5 Flash. Maximum output per response: Mistral Large 3 up to 262,144, Step 3.5 Flash up to 256,000, GPT-5.1 Codex mini up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 3 accepts text and images; Step 3.5 Flash accepts text; GPT-5.1 Codex mini accepts text and images. Mistral Large 3 handles the widest range of inputs.
Are any of these open source?
Mistral Large 3 and Step 3.5 Flash publishes its weights and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
Step 3.5 Flash is the newest, released Jan 29, 2026. Mistral Large 3 came out Dec 2, 2025; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: Mistral Large 3 Nov 2024, Step 3.5 Flash Jan 2025, GPT-5.1 Codex mini Sep 30, 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
