Mistral Large vs Mixtral 8x7B Instruct v0.1
Mistral Large comes out ahead, 44 to 34 on our weighted score, though Mixtral 8x7B Instruct v0.1 is 36% cheaper per token.
- Our pick
Mistral AIMistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
- Mistral AI
Mixtral 8x7B Instruct v0.1
34/100- ECI118.4
- Price$0.444 / $0.579
- Context33K
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Make it a three-way comparison.
Mistral Large is our pick
Mistral Large is the better all-round choice, scoring 44/100 against Mixtral 8x7B Instruct v0.1 (34). It leads on capability, inputs & features and context window. Mixtral 8x7B Instruct v0.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral LargeCapabilities Index (ECI): Mistral Large 122.0 · Mixtral 8x7B Instruct v0.1 118.4
- Lowest priceMixtral 8x7B Instruct v0.1Mixtral 8x7B Instruct v0.1 $0.478 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral LargeMistral Large 128,000 · Mixtral 8x7B Instruct v0.1 32,768 tokens
- Widest inputsMistral LargeMistral Large: Text, PDFs · Mixtral 8x7B Instruct v0.1: Text
- Self-hostingMixtral 8x7B Instruct v0.1Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Mistral Large | Mixtral 8x7B Instruct v0.1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 38 |
| Price | 25% | 53 | 62 |
| Inputs & features | 15% | 45 | 0 |
| Context window | 10% | 24 | 0 |
| Overall | 100% | 44/100 | 34/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral LargeMistral AI | Mixtral 8x7B Instruct v0.1Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 122.0 (best) | 118.4 |
| ECI rank | #153 of 165 (best) | #160 of 165 |
| GPQA DiamondGraduate-level science questions | 38.8% (best) | 30.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.9% | — |
| Price per million tokens | ||
| Input | $0.50 | $0.444 (best) |
| Output | $1.50 | $0.579 (best) |
| Cached input | $0.05 | — |
| Blended (3:1) | $0.75 | $0.478 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 2 providers |
| Limits | ||
| Context window | 128,000 tokens (best) | 32,768 tokens |
| Max output | 102,400 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | No |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | OpenApache 2.0 |
| API model ID | mistral-large-latest | — |
| API providers | 11 (best) | 2 |
| Released | Feb 26, 2024 | Dec 11, 2023 |
| Knowledge cutoff | Nov 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$8.00
- Mixtral 8x7B Instruct v0.1$5.60
Which should you choose?
Which is better: Mistral Large or Mixtral 8x7B Instruct v0.1?
Mistral Large is the better all-round choice, scoring 44/100 against Mixtral 8x7B Instruct v0.1 (34). It leads on capability, inputs & features and context window. Mixtral 8x7B Instruct v0.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large or Mixtral 8x7B Instruct v0.1?
Mixtral 8x7B Instruct v0.1 is cheaper at $0.444 input / $0.579 output per million tokens (median across 2 API providers). Mistral Large 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 $0.478 per million tokens for Mixtral 8x7B Instruct v0.1 versus $0.75 for Mistral Large (1.6× as much).
Which scores higher on benchmarks?
Mistral Large scores higher on the Capabilities Index (ECI): Mistral Large 122.0 (#153 of 165) and Mixtral 8x7B Instruct v0.1 118.4 (#160 of 165). The confidence ranges of the top two overlap (115.7–124.8 vs 110.9–121.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 38.8%, Mixtral 8x7B Instruct v0.1 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large and Mixtral 8x7B Instruct v0.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large leads, which tends to carry over to coding, but test on your own codebase. Note that Mixtral 8x7B Instruct v0.1 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Mistral Large has the largest context window at 128,000 tokens, against 32,768 for Mixtral 8x7B Instruct v0.1. Maximum output per response: Mistral Large up to 102,400, Mixtral 8x7B Instruct v0.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Mistral Large accepts text and PDFs; Mixtral 8x7B Instruct v0.1 accepts text. Mistral Large handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B Instruct v0.1 publishes its weights (Apache 2.0) and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Mistral Large is the newest, released Feb 26, 2024. Mixtral 8x7B Instruct v0.1 came out Dec 11, 2023. Knowledge cutoff: Mistral Large Nov 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 Nov 2, 2026.
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