Mistral Large 3 vs Nova 2 Lite vs Trinity Nano Preview
Nova 2 Lite comes out ahead, 72 to 45 and 25 on our weighted score, though Mistral Large 3 is 20% cheaper per token.
Mistral AIMistral Large 3
45/100- ECI—
- Price$0.50 / $1.50
- Context262K
- Our pick
AmazonNova 2 Lite
72/100- ECI—
- Price$0.33 / $2.75
- Context1M
Arcee AITrinity Nano Preview
25/100- ECI—
- Price—
- Context131K
Nova 2 Lite is our pick
Nova 2 Lite is the better all-round choice, scoring 72/100 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 priceMistral Large 3Mistral Large 3 $0.75 · Nova 2 Lite $0.935 per 1M tokens (3:1 blend) · Trinity Nano Preview unpriced
- Longest contextNova 2 LiteNova 2 Lite 1,000,000 · Mistral Large 3 262,144 · Trinity Nano Preview 131,072 tokens
- Widest inputsNova 2 LiteMistral Large 3: Text, Images · Nova 2 Lite: Text, Images, PDFs, Video · Trinity Nano Preview: Text
- Self-hostingMistral Large 3 and Trinity Nano PreviewPublishes downloadable weights (OpenMDW-1.1)
| Measure | Weight | Mistral Large 3 | Nova 2 Lite | Trinity Nano Preview |
|---|---|---|---|---|
| Inputs & features | 60% | 50 | 80 | 25 |
| Context window | 40% | 37 | 60 | 24 |
| Overall | 100% | 45/100 | 72/100 | 25/100 |
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 | Nova 2 LiteAmazon | Trinity Nano PreviewArcee AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.33 (best) | — |
| Output | $1.50 (best) | $2.75 | — |
| Cached input | $0.05 (best) | $0.083 | — |
| Blended (3:1) | $0.75 (best) | $0.935 | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Official Mistral API | Official Amazon Bedrock API | — |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 262,144 tokens (best) | 65,536 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | Yeslow · medium · high | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenOpenMDW-1.1 |
| API model ID | mistral-large-2512 | amazon.nova-2-lite-v1:0 | — |
| API providers | 13 (best) | 2 | — |
| Released | Dec 2, 2025 | Dec 2, 2025 | Dec 1, 2025 |
| Knowledge cutoff | Nov 2024 | Oct 2025 | — |
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
- Nova 2 Lite$8.80
- Trinity Nano Preview—
Which should you choose?
Which is better: Mistral Large 3, Nova 2 Lite or Trinity Nano Preview?
Nova 2 Lite is the better all-round choice, scoring 72/100 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, Nova 2 Lite or Trinity Nano Preview?
Mistral Large 3 is cheaper at $0.50 input / $1.50 output per million tokens (official Mistral API price). Nova 2 Lite costs $0.33 input / $2.75 output per million tokens (official Amazon Bedrock API price). At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Mistral Large 3 versus $0.935 for Nova 2 Lite (1.2× 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, Nova 2 Lite has not been scored yet and Trinity Nano Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 3, Nova 2 Lite and Trinity Nano Preview 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?
Nova 2 Lite has the largest context window at 1,000,000 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, Nova 2 Lite up to 65,536, Trinity Nano Preview up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 3 accepts text and images; Nova 2 Lite accepts text, images, PDFs and video; Trinity Nano Preview accepts text. Nova 2 Lite 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; Nova 2 Lite is proprietary.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. Nova 2 Lite came out Dec 2, 2025; Trinity Nano Preview came out Dec 1, 2025. Knowledge cutoff: Mistral Large 3 Nov 2024, Nova 2 Lite Oct 2025.
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.
