Mistral Large 2.1 vs Mixtral 8x22B Instruct
Mistral Large 2.1 comes out ahead, 38 to 34 on our weighted score.
- Our pick
Mistral AIMistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
- Mistral AI
Mixtral 8x22B Instruct
34/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
Add a model
Make it a three-way comparison.
Mistral Large 2.1 is our pick
Mistral Large 2.1 is the better all-round choice, scoring 38/100 against Mixtral 8x22B Instruct (34). It leads on capability and context window. Mixtral 8x22B Instruct wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Mixtral 8x22B Instruct 122.0
- Lowest priceSame priceMistral Large 2.1 $3.00 · Mixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Mixtral 8x22B Instruct 65,536 tokens
- Widest inputsMixtral 8x22B InstructMistral Large 2.1: Text · Mixtral 8x22B Instruct: Text, PDFs
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Large 2.1 | Mixtral 8x22B Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 50 | 42 |
| Price | 25% | 26 | 26 |
| Inputs & features | 15% | 25 | 35 |
| Context window | 10% | 25 | 12 |
| Overall | 100% | 38/100 | 34/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Large 2.1Mistral AI | Mixtral 8x22B InstructMistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 128.6 (best) | 122.0 |
| ECI rank | #142 of 165 (best) | #155 of 165 |
| GPQA DiamondGraduate-level science questions | 51.3% (best) | 34.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% | — |
| Price per million tokens | ||
| Input | $2.00 | $2.00 |
| Output | $6.00 | $6.00 |
| Cached input | — | — |
| Blended (3:1) | $3.00 | $3.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 5 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 65,536 tokens |
| Max output | 16,384 tokens | 52,428 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 2 | 5 (best) |
| Released | Nov 18, 2024 | Apr 17, 2024 |
| Knowledge cutoff | Nov 2024 | Jan 31, 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 2.1$32.00
- Mixtral 8x22B Instruct$32.00
Which should you choose?
Which is better: Mistral Large 2.1 or Mixtral 8x22B Instruct?
Mistral Large 2.1 is the better all-round choice, scoring 38/100 against Mixtral 8x22B Instruct (34). It leads on capability and context window. Mixtral 8x22B Instruct wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large 2.1 or Mixtral 8x22B Instruct?
Mistral Large 2.1 and Mixtral 8x22B Instruct cost the same: $2.00 input / $6.00 output per million tokens.
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 115.7–124.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2.1 and Mixtral 8x22B Instruct 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 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Mistral Large 2.1 up to 16,384, Mixtral 8x22B Instruct up to 52,428 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2.1 accepts text; Mixtral 8x22B Instruct accepts text and PDFs. Mixtral 8x22B Instruct handles the widest range of inputs.
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. Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Mixtral 8x22B Instruct Jan 31, 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 Nov 2, 2026.
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