ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large 2.1 vs Mistral Large 4 vs Claude Haiku 3.5

Mistral Large 4 comes out ahead, 67 to 46 and 38 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.6
    • Price$2.00 / $6.00
    • Context131K
  2. Our pick

    Mistral AI

    Mistral Large 4

    Released Oct 6, 2026NewBeta

    67/100
    • ECI150.6
    • Price$0.70 / $2.10
    • Context1.05M
  3. Anthropic

    Claude Haiku 3.5

    Released Oct 22, 2024

    46/100
    • ECI127.0
    • Price$0.80 / $4.00
    • Context200K
01 — Verdict

Mistral Large 4 is our pick

Mistral Large 4 is the better all-round choice, scoring 67/100 against Claude Haiku 3.5 (46) and Mistral Large 2.1 (38). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Large 4Capabilities Index (ECI): Mistral Large 4 150.6 · Mistral Large 2.1 128.6 · Claude Haiku 3.5 127.0
  • Lowest priceMistral Large 4Mistral Large 4 $1.05 · Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 4Mistral Large 4 1,048,576 · Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 tokens
  • Widest inputsClaude Haiku 3.5Mistral Large 2.1: Text · Mistral Large 4: Text, Images · Claude Haiku 3.5: Text, Images, PDFs
  • Self-hostingMistral Large 2.1Publishes downloadable weights
How the score is built
MeasureWeightMistral Large 2.1Mistral Large 4Claude Haiku 3.5
CapabilityCapabilities Index (ECI)50%507748
Price25%264738
Inputs & features15%257060
Context window10%256132
Overall100%38/10067/10046/100
02 — Side by side

Every spec in one table

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

Mistral Large 2.1 vs Mistral Large 4 vs Claude Haiku 3.5 specifications side by side
SpecificationMistral Large 2.1Mistral AIMistral Large 4Mistral AIClaude Haiku 3.5Anthropic
Capability
Capabilities Index (ECI)128.6150.6 (best)127.0
ECI rank#142 of 165#57 of 165 (best)#147 of 165
GPQA DiamondGraduate-level science questions51.3%88.1% (best)38.1%
FrontierMath Tiers 1–3Research-level mathematics—58.6%—
OTIS Mock AIME 2024–2025Competition mathematics7.8%98.3% (best)4.3%
SimpleQA VerifiedShort factual questions—20.0%—
Price per million tokens
Input$2.00$0.70 (best)$0.80
Output$6.00$2.10 (best)$4.00
Cached input—$0.07—
Blended (3:1)$3.00$1.05 (best)$1.60
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Mistral APIMedian of 3 providers
Limits
Context window131,072 tokens1,048,576 tokens (best)200,000 tokens
Max output16,384 tokens262,144 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoYeslow · medium · highNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryProprietary
API model ID—mistral-large-4—
API providers215 (best)4
ReleasedNov 18, 2024Oct 6, 2026Oct 22, 2024
Knowledge cutoffNov 2024—Jul 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.

  • Mistral Large 2.1$32.00
  • Mistral Large 4$11.20
  • Claude Haiku 3.5$16.00
04 — Questions

Which should you choose?

Which is better: Mistral Large 2.1, Mistral Large 4 or Claude Haiku 3.5?

Mistral Large 4 is the better all-round choice, scoring 67/100 against Claude Haiku 3.5 (46) and Mistral Large 2.1 (38). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large 2.1, Mistral Large 4 or Claude Haiku 3.5?

Mistral Large 4 is cheaper at $0.70 input / $2.10 output per million tokens (official Mistral API price). Claude Haiku 3.5 costs $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). At a typical mix of three input tokens to one output token, that is $1.05 per million tokens for Mistral Large 4 versus $1.60 for Claude Haiku 3.5 (1.5× as much) and $3.00 for Mistral Large 2.1 (2.9× as much).

Which scores higher on benchmarks?

Mistral Large 4 scores higher on the Capabilities Index (ECI): Mistral Large 4 150.6 (#57 of 165), Mistral Large 2.1 128.6 (#142 of 165) and Claude Haiku 3.5 127.0 (#147 of 165). Their confidence ranges do not overlap (147.4–153.5 vs 124.3–130.7), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Large 4 88.1%, Mistral Large 2.1 51.3%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Mistral Large 4 98.3%, 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, Mistral Large 4 and Claude Haiku 3.5 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 4 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?

Mistral Large 4 has the largest context window at 1,048,576 tokens, against 200,000 for Claude Haiku 3.5 and 131,072 for Mistral Large 2.1. Maximum output per response: Mistral Large 2.1 up to 16,384, Mistral Large 4 up to 262,144, Claude Haiku 3.5 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 2.1 accepts text; Mistral Large 4 accepts text and images; 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; Mistral Large 4 and Claude Haiku 3.5 is proprietary.

Which is newer?

Mistral Large 4 is the newest, released Oct 6, 2026. Mistral Large 2.1 came out 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 Nov 2, 2026.