Mistral Nemo vs Mistral Large 2.1
Mistral Nemo comes out ahead, 48 to 38 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AIMistral Nemo
48/100- ECI118.7
- Price$0.15 / $0.15
- Context128K
- Mistral AI
Mistral Large 2.1
38/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
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Make it a three-way comparison.
Mistral Nemo is our pick
Mistral Nemo is the better all-round choice, scoring 48/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.5 · Mistral Nemo 118.7
- Lowest priceMistral NemoMistral Nemo $0.15 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Mistral Nemo 128,000 tokens
- Widest inputsSame inputsMistral Nemo: Text · Mistral Large 2.1: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Nemo | Mistral Large 2.1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 39 | 51 |
| Price | 25% | 89 | 27 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 24 | 24 |
| Overall | 100% | 48/100 | 38/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral NemoMistral AI | Mistral Large 2.1Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 118.7 | 128.5 (best) |
| ECI rank | #140 of 148 | #130 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 29.9% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% |
| Price per million tokens | ||
| Input | $0.15 (best) | $2.00 |
| Output | $0.15 (best) | $6.00 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $3.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Mistral API |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 128,000 tokens (best) | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | mistral-nemo | mistral-large-2411 |
| API providers | 5 (best) | 2 |
| Released | Jul 1, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jul 2024 | Nov 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 Nemo$1.80
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Mistral Nemo or Mistral Large 2.1?
Mistral Nemo is the better all-round choice, scoring 48/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Nemo or Mistral Large 2.1?
Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Mistral Large 2.1 costs $2.00 input / $6.00 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 Mistral Nemo versus $3.00 for Mistral Large 2.1 (20× as much).
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.5 (#130 of 148) and Mistral Nemo 118.7 (#140 of 148). Their confidence ranges do not overlap (123.8–130.8 vs 111.3–121.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mistral Nemo 29.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Nemo and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large 2.1 has the largest context window at 131,072 tokens, against 128,000 for Mistral Nemo. Maximum output per response: Mistral Nemo up to 128,000, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mistral Nemo accepts text; Mistral Large 2.1 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 2024, Mistral Large 2.1 Nov 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.
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