Mistral Large 2.1 vs Claude Haiku 3.5
Claude Haiku 3.5 comes out ahead, 49 to 42 on our weighted score.
Mistral AIMistral Large 2.1
42/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
- Our pick
AnthropicClaude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
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Make it a three-way comparison.
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Mistral Large 2.1 (42). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.5 · Claude Haiku 3.5 127.2
- Lowest priceMistral Large 2.1Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 tokens
- Widest inputsClaude Haiku 3.5Mistral Large 2.1: Text · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingMistral Large 2.1Publishes downloadable weights
| Measure | Weight | Mistral Large 2.1 | Claude Haiku 3.5 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 51 | 49 |
| Inputs & features | 20% | 25 | 60 |
| Context window | 13% | 24 | 32 |
| Overall | 100% | 42/100 | 49/100 |
Left out because at least one model lacks the data: 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 2.1Mistral AI | Claude Haiku 3.5Anthropic |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 128.5 (best) | 127.2 |
| ECI rank | #130 of 148 (best) | #134 of 148 |
| GPQA DiamondGraduate-level science questions | 51.3% (best) | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% (best) | 4.3% |
| Price per million tokens | ||
| Input | $2.00 | — |
| Output | $6.00 | — |
| Cached input | — | — |
| Blended (3:1) | $3.00 | — |
| Long-context rate | Same rate | — |
| Price source | Official Mistral API | — |
| Limits | ||
| Context window | 131,072 tokens | 200,000 tokens (best) |
| Max output | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | mistral-large-2411 | — |
| API providers | 2 | — |
| Released | Nov 18, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Nov 2024 | Jul 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
- Claude Haiku 3.5—
Which should you choose?
Which is better: Mistral Large 2.1 or Claude Haiku 3.5?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Mistral Large 2.1 (42). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Mistral Large 2.1 or Claude Haiku 3.5?
Mistral Large 2.1 is cheaper at $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 $3.00 per million tokens for Mistral Large 2.1 versus . Claude Haiku 3.5 has no published per-token price.
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 Claude Haiku 3.5 127.2 (#134 of 148). The confidence ranges of the top two overlap (123.8–130.8 vs 120.7–129.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Claude Haiku 3.5 4.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2.1 and Claude Haiku 3.5 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?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2.1. Maximum output per response: Mistral Large 2.1 up to 16,384, Claude Haiku 3.5 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2.1 accepts text; Claude Haiku 3.5 accepts text, images and PDFs. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Mistral Large 2.1 publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Claude Haiku 3.5 came out Oct 22, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Claude Haiku 3.5 Jul 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 Oct 4, 2026.
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