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Comparison · 3 models · Updated Oct 4, 2026

Claude Haiku 3 vs Mistral Nemo vs Qwen2.5 7B Instruct

Too close to call on our weighted score (Mistral Nemo 48, Claude Haiku 3 47, Qwen2.5 7B Instruct 44). The right pick depends on what you value most.

  1. Anthropic

    Claude Haiku 3

    Released Mar 13, 2024

    47/100
    • ECI118.4
    • Price$0.25 / $1.25
    • Context200K
    Full specs Remove Claude Haiku 3

  2. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo

  3. Alibaba (Qwen)

    Qwen2.5 7B Instruct

    Released Sep 19, 2024

    44/100
    • ECI118.5
    • Price$0.175 / $0.70
    • Context131K
    Full specs Remove Qwen2.5 7B Instruct
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Mistral Nemo 48/100, Claude Haiku 3 47/100, Qwen2.5 7B Instruct 44/100), so choose by what matters most for your work: Mistral Nemo for raw capability and Claude Haiku 3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral NemoCapabilities Index (ECI): Mistral Nemo 118.7 · Qwen2.5 7B Instruct 118.5 · Claude Haiku 3 118.4
  • Lowest priceMistral NemoMistral Nemo $0.15 · Qwen2.5 7B Instruct $0.306 · Claude Haiku 3 $0.50 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Qwen2.5 7B Instruct 131,072 · Mistral Nemo 128,000 tokens
  • Widest inputsClaude Haiku 3Claude Haiku 3: Text, Images, PDFs · Mistral Nemo: Text · Qwen2.5 7B Instruct: Text
  • Self-hostingMistral Nemo and Qwen2.5 7B InstructPublishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 3Mistral NemoQwen2.5 7B Instruct
CapabilityCapabilities Index (ECI)50%383938
Price25%648974
Inputs & features15%602525
Context window10%322424
Overall100%47/10048/10044/100
02 — Side by side

Every spec in one table

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

Claude Haiku 3 vs Mistral Nemo vs Qwen2.5 7B Instruct specifications side by side
SpecificationClaude Haiku 3AnthropicMistral NemoMistral AIQwen2.5 7B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)118.4118.7 (best)118.5
ECI rank#143 of 148#140 of 148 (best)#141 of 148
GPQA DiamondGraduate-level science questions36.3% (best)29.9%35.5%
OTIS Mock AIME 2024–2025Competition mathematics1.8%—2.5% (best)
Price per million tokens
Input$0.25$0.15 (best)$0.175
Output$1.25$0.15 (best)$0.70
Cached input———
Blended (3:1)$0.50$0.15 (best)$0.306
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Mistral APIOfficial Alibaba API
Limits
Context window200,000 tokens (best)128,000 tokens131,072 tokens
Max output4,096 tokens128,000 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenOpen
API model ID—mistral-nemoqwen2-5-7b-instruct
API providers25 (best)1
ReleasedMar 13, 2024Jul 1, 2024Sep 19, 2024
Knowledge cutoffAug 31, 2023Jul 2024Apr 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$5.00
  • Mistral Nemo$1.80
  • Qwen2.5 7B Instruct$3.15
04 — Questions

Which should you choose?

Which is better: Claude Haiku 3, Mistral Nemo or Qwen2.5 7B Instruct?

It is close. Our weighted score puts them within a point (Mistral Nemo 48/100, Claude Haiku 3 47/100, Qwen2.5 7B Instruct 44/100), so choose by what matters most for your work: Mistral Nemo for raw capability and Claude Haiku 3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Haiku 3, Mistral Nemo or Qwen2.5 7B Instruct?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Qwen2.5 7B Instruct costs $0.175 input / $0.70 output per million tokens (official Alibaba API price); Claude Haiku 3 costs $0.25 input / $1.25 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Nemo versus $0.306 for Qwen2.5 7B Instruct (2× as much) and $0.50 for Claude Haiku 3 (3.3× as much).

Which scores higher on benchmarks?

Mistral Nemo scores higher on the Capabilities Index (ECI): Mistral Nemo 118.7 (#140 of 148), Qwen2.5 7B Instruct 118.5 (#141 of 148) and Claude Haiku 3 118.4 (#143 of 148). The confidence ranges of the top two overlap (111.3–121.5 vs 110.7–121.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Haiku 3 36.3%, Qwen2.5 7B Instruct 35.5%, Mistral Nemo 29.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 3, Mistral Nemo and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Nemo 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 has the largest context window at 200,000 tokens, against 131,072 for Qwen2.5 7B Instruct and 128,000 for Mistral Nemo. Maximum output per response: Claude Haiku 3 up to 4,096, Mistral Nemo up to 128,000, Qwen2.5 7B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 3 accepts text, images and PDFs; Mistral Nemo accepts text; Qwen2.5 7B Instruct accepts text. Claude Haiku 3 handles the widest range of inputs.

Are any of these open source?

Mistral Nemo and Qwen2.5 7B Instruct publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.

Which is newer?

Qwen2.5 7B Instruct is the newest, released Sep 19, 2024. Mistral Nemo came out Jul 1, 2024; Claude Haiku 3 came out Mar 13, 2024. Knowledge cutoff: Claude Haiku 3 Aug 31, 2023, Mistral Nemo Jul 2024, Qwen2.5 7B Instruct Apr 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.

05 — Keep comparing

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