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Comparison · 3 models · Updated Oct 4, 2026

Claude Haiku 3 vs Qwen2.5 32B Instruct vs Mixtral 8x7B

Claude Haiku 3 comes out ahead, 47 to 43 and 37 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Anthropic

    Claude Haiku 3

    Released Mar 13, 2024

    47/100
    • ECI118.4
    • Price$0.25 / $1.25
    • Context200K
  2. Alibaba (Qwen)

    Qwen2.5 32B Instruct

    Released Sep 17, 2024

    43/100
    • ECI128.5
    • Price$0.70 / $2.80
    • Context131K
  3. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

    37/100
    • ECI118.5
    • Price$0.70 / $0.70
    • Context32K
01 — Verdict

Claude Haiku 3 is our pick

Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 32B Instruct (43) and Mixtral 8x7B (37). It leads on price, inputs & features and context window. Qwen2.5 32B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 32B InstructCapabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mixtral 8x7B 118.5 · Claude Haiku 3 118.4
  • Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Mixtral 8x7B $0.70 · Qwen2.5 32B Instruct $1.23 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Qwen2.5 32B Instruct 131,072 · Mixtral 8x7B 32,000 tokens
  • Widest inputsClaude Haiku 3Claude Haiku 3: Text, Images, PDFs · Qwen2.5 32B Instruct: Text · Mixtral 8x7B: Text
  • Self-hostingQwen2.5 32B Instruct and Mixtral 8x7BPublishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 3Qwen2.5 32B InstructMixtral 8x7B
CapabilityCapabilities Index (ECI)50%385138
Price25%644657
Inputs & features15%602525
Context window10%32240
Overall100%47/10043/10037/100
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 Qwen2.5 32B Instruct vs Mixtral 8x7B specifications side by side
SpecificationClaude Haiku 3AnthropicQwen2.5 32B InstructAlibaba (Qwen)Mixtral 8x7BMistral AI
Capability
Capabilities Index (ECI)118.4128.5 (best)118.5
ECI rank#143 of 148#131 of 148 (best)#142 of 148
GPQA DiamondGraduate-level science questions36.3%46.1% (best)30.6%
OTIS Mock AIME 2024–2025Competition mathematics1.8%7.4% (best)—
Price per million tokens
Input$0.25 (best)$0.70$0.70
Output$1.25$2.80$0.70 (best)
Cached input———
Blended (3:1)$0.50 (best)$1.23$0.70
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Alibaba APIOfficial Mistral API
Limits
Context window200,000 tokens (best)131,072 tokens32,000 tokens
Max output4,096 tokens8,192 tokens32,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenOpen
API model ID—qwen2-5-32b-instructopen-mixtral-8x7b
API providers2 (best)11
ReleasedMar 13, 2024Sep 17, 2024Dec 11, 2023
Knowledge cutoffAug 31, 2023Apr 2024Jan 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
  • Qwen2.5 32B Instruct$12.60
  • Mixtral 8x7B$8.40
04 — Questions

Which should you choose?

Which is better: Claude Haiku 3, Qwen2.5 32B Instruct or Mixtral 8x7B?

Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 32B Instruct (43) and Mixtral 8x7B (37). It leads on price, inputs & features and context window. Qwen2.5 32B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Haiku 3, Qwen2.5 32B Instruct or Mixtral 8x7B?

Claude Haiku 3 is cheaper at $0.25 input / $1.25 output per million tokens (median across 2 API providers). Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price); Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.50 per million tokens for Claude Haiku 3 versus $0.70 for Mixtral 8x7B (1.4× as much) and $1.23 for Qwen2.5 32B Instruct (2.5× as much).

Which scores higher on benchmarks?

Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148), Mixtral 8x7B 118.5 (#142 of 148) and Claude Haiku 3 118.4 (#143 of 148). Their confidence ranges do not overlap (123.5–130.0 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Claude Haiku 3 36.3%, Mixtral 8x7B 30.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 3, Qwen2.5 32B Instruct and Mixtral 8x7B yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct 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 32B Instruct and 32,000 for Mixtral 8x7B. Maximum output per response: Claude Haiku 3 up to 4,096, Qwen2.5 32B Instruct up to 8,192, Mixtral 8x7B up to 32,000 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 3 accepts text, images and PDFs; Qwen2.5 32B Instruct accepts text; Mixtral 8x7B accepts text. Claude Haiku 3 handles the widest range of inputs.

Are any of these open source?

Qwen2.5 32B Instruct and Mixtral 8x7B publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.

Which is newer?

Qwen2.5 32B Instruct is the newest, released Sep 17, 2024. Claude Haiku 3 came out Mar 13, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Claude Haiku 3 Aug 31, 2023, Qwen2.5 32B Instruct Apr 2024, Mixtral 8x7B Jan 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.