Mistral Large 3 vs Trinity Nano Preview vs GPT-5.1 Codex mini
GPT-5.1 Codex mini comes out ahead, 60 to 45 and 25 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 3
45/100- ECI—
- Price$0.50 / $1.50
- Context262K
Arcee AITrinity Nano Preview
25/100- ECI—
- Price—
- Context131K
- Our pick
OpenAIGPT-5.1 Codex mini
60/100- ECI—
- Price$0.25 / $2.00
- Context400K
GPT-5.1 Codex mini is our pick
GPT-5.1 Codex mini is the better all-round choice, scoring 60/100 against Mistral Large 3 (45) and Trinity Nano Preview (25). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 priceGPT-5.1 Codex miniGPT-5.1 Codex mini $0.688 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend) · Trinity Nano Preview unpriced
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Large 3 262,144 · Trinity Nano Preview 131,072 tokens
- Widest inputsMistral Large 3 and GPT-5.1 Codex miniMistral Large 3: Text, Images · Trinity Nano Preview: Text · GPT-5.1 Codex mini: Text, Images
- Self-hostingMistral Large 3 and Trinity Nano PreviewPublishes downloadable weights (OpenMDW-1.1)
| Measure | Weight | Mistral Large 3 | Trinity Nano Preview | GPT-5.1 Codex mini |
|---|---|---|---|---|
| Inputs & features | 60% | 50 | 25 | 70 |
| Context window | 40% | 37 | 24 | 44 |
| Overall | 100% | 45/100 | 25/100 | 60/100 |
Left out because at least one model lacks the data: capability and price. 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 | Trinity Nano PreviewArcee AI | GPT-5.1 Codex miniOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | — | $0.25 (best) |
| Output | $1.50 (best) | — | $2.00 |
| Cached input | $0.05 | — | — |
| Blended (3:1) | $0.75 | — | $0.688 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Mistral API | — | Median of 10 providers |
| Limits | |||
| Context window | 262,144 tokens | 131,072 tokens | 400,000 tokens (best) |
| Max output | 262,144 tokens (best) | 131,072 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenOpenMDW-1.1 | Proprietary |
| API model ID | mistral-large-2512 | — | — |
| API providers | 13 (best) | — | 10 |
| Released | Dec 2, 2025 | Dec 1, 2025 | Nov 13, 2025 |
| Knowledge cutoff | Nov 2024 | — | 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
- Trinity Nano Preview—
- GPT-5.1 Codex mini$6.50
Which should you choose?
Which is better: Mistral Large 3, Trinity Nano Preview or GPT-5.1 Codex mini?
GPT-5.1 Codex mini is the better all-round choice, scoring 60/100 against Mistral Large 3 (45) and Trinity Nano Preview (25). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Mistral Large 3, Trinity Nano Preview or GPT-5.1 Codex mini?
GPT-5.1 Codex mini is cheaper at $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 $0.688 per million tokens for GPT-5.1 Codex mini versus $0.75 for Mistral Large 3 (1.1× as much). Trinity Nano Preview has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Large 3 has not been scored yet, Trinity Nano Preview 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, Trinity Nano Preview 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 131,072 for Trinity Nano Preview. Maximum output per response: Mistral Large 3 up to 262,144, Trinity Nano Preview up to 131,072, 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; Trinity Nano Preview 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 Trinity Nano Preview publishes its weights (OpenMDW-1.1) and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. Trinity Nano Preview came out Dec 1, 2025; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: Mistral Large 3 Nov 2024, 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.
