ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Claude Haiku 3.5 vs Mistral Large 2.1 vs Mistral Large 2407

Claude Haiku 3.5 comes out ahead, 46 to 39 and 38 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Anthropic

    Claude Haiku 3.5

    Released Oct 22, 2024

    46/100
    • ECI127.0
    • Price$0.80 / $4.00
    • Context200K
  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.6
    • Price$2.00 / $6.00
    • Context131K
  3. Mistral AI

    Mistral Large 2407

    Released Jul 24, 2024

    39/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
01 — Verdict

Claude Haiku 3.5 is our pick

Claude Haiku 3.5 is the better all-round choice, scoring 46/100 against Mistral Large 2407 (39) and Mistral Large 2.1 (38). It leads on price, inputs & features and context window. 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 · Mistral Large 2407 127.6 · Claude Haiku 3.5 127.0
  • Lowest priceClaude Haiku 3.5Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 · Mistral Large 2407 $3.00 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 · Mistral Large 2407 131,072 tokens
  • Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Mistral Large 2.1: Text · Mistral Large 2407: Text, PDFs
  • Self-hostingMistral Large 2.1 and Mistral Large 2407Publishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 3.5Mistral Large 2.1Mistral Large 2407
CapabilityCapabilities Index (ECI)50%485049
Price25%382626
Inputs & features15%602535
Context window10%322525
Overall100%46/10038/10039/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Claude Haiku 3.5 vs Mistral Large 2.1 vs Mistral Large 2407 specifications side by side
SpecificationClaude Haiku 3.5AnthropicMistral Large 2.1Mistral AIMistral Large 2407Mistral AI
Capability
Capabilities Index (ECI)127.0128.6 (best)127.6
ECI rank#147 of 165#142 of 165 (best)#144 of 165
GPQA DiamondGraduate-level science questions38.1%51.3% (best)49.0%
OTIS Mock AIME 2024–2025Competition mathematics4.3%7.8%8.5% (best)
Price per million tokens
Input$0.80 (best)$2.00$2.00
Output$4.00 (best)$6.00$6.00
Cached input———
Blended (3:1)$1.60 (best)$3.00$3.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 2 providersMedian of 5 providers
Limits
Context window200,000 tokens (best)131,072 tokens131,072 tokens
Max output8,192 tokens16,384 tokens104,857 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenOpen
API model ID———
API providers425 (best)
ReleasedOct 22, 2024Nov 18, 2024Jul 24, 2024
Knowledge cutoffJul 31, 2024Nov 2024Mar 31, 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Claude Haiku 3.5$16.00
  • Mistral Large 2.1$32.00
  • Mistral Large 2407$32.00
04 — Questions

Which should you choose?

Which is better: Claude Haiku 3.5, Mistral Large 2.1 or Mistral Large 2407?

Claude Haiku 3.5 is the better all-round choice, scoring 46/100 against Mistral Large 2407 (39) and Mistral Large 2.1 (38). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Haiku 3.5, Mistral Large 2.1 or Mistral Large 2407?

Claude Haiku 3.5 is cheaper at $0.80 input / $4.00 output per million tokens (median across 3 API providers). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers); Mistral Large 2407 costs $2.00 input / $6.00 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $1.60 per million tokens for Claude Haiku 3.5 versus $3.00 for Mistral Large 2.1 (1.9× as much) and $3.00 for Mistral Large 2407 (1.9× as much).

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), Mistral Large 2407 127.6 (#144 of 165) and Claude Haiku 3.5 127.0 (#147 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 123.3–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mistral Large 2407 49.0%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, 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 Claude Haiku 3.5, Mistral Large 2.1 and Mistral Large 2407 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. All three 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 and 131,072 for Mistral Large 2407. Maximum output per response: Claude Haiku 3.5 up to 8,192, Mistral Large 2.1 up to 16,384, Mistral Large 2407 up to 104,857 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 3.5 accepts text, images and PDFs; Mistral Large 2.1 accepts text; Mistral Large 2407 accepts text and PDFs. Claude Haiku 3.5 handles the widest range of inputs.

Are any of these open source?

Mistral Large 2.1 and Mistral Large 2407 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; Mistral Large 2407 came out Jul 24, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Mistral Large 2.1 Nov 2024, Mistral Large 2407 Mar 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.