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Comparison · 2 models · Updated Oct 4, 2026

Mixtral 8x7B vs Qwen2.5 7B Instruct

Qwen2.5 7B Instruct comes out ahead, 44 to 37 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

    37/100
    • ECI118.5
    • Price$0.70 / $0.70
    • Context32K
    Full specs Remove Mixtral 8x7B
  2. Our pick

    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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen2.5 7B Instruct is our pick

Qwen2.5 7B Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x7B (37). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 7B InstructCapabilities Index (ECI): Qwen2.5 7B Instruct 118.5 · Mixtral 8x7B 118.5
  • Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.306 · Mixtral 8x7B $0.70 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Mixtral 8x7B 32,000 tokens
  • Widest inputsSame inputsMixtral 8x7B: Text · Qwen2.5 7B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMixtral 8x7BQwen2.5 7B Instruct
CapabilityCapabilities Index (ECI)50%3838
Price25%5774
Inputs & features15%2525
Context window10%024
Overall100%37/10044/100
02 — Side by side

Every spec in one table

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

Mixtral 8x7B vs Qwen2.5 7B Instruct specifications side by side
SpecificationMixtral 8x7BMistral AIQwen2.5 7B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)118.5118.5 (best)
ECI rank#142 of 148#141 of 148 (best)
GPQA DiamondGraduate-level science questions30.6%35.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics—2.5%
Price per million tokens
Input$0.70$0.175 (best)
Output$0.70$0.70
Cached input——
Blended (3:1)$0.70$0.306 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba API
Limits
Context window32,000 tokens131,072 tokens (best)
Max output32,000 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDopen-mixtral-8x7bqwen2-5-7b-instruct
API providers11
ReleasedDec 11, 2023Sep 19, 2024
Knowledge cutoffJan 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.

  • Mixtral 8x7B$8.40
  • Qwen2.5 7B Instruct$3.15
04 — Questions

Which should you choose?

Which is better: Mixtral 8x7B or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x7B (37). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mixtral 8x7B or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper at $0.175 input / $0.70 output per million tokens (official Alibaba API price). Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.306 per million tokens for Qwen2.5 7B Instruct versus $0.70 for Mixtral 8x7B (2.3× as much).

Which scores higher on benchmarks?

Qwen2.5 7B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 7B Instruct 118.5 (#141 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (110.7–121.3 vs 111.3–121.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 7B Instruct 35.5%, Mixtral 8x7B 30.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Mixtral 8x7B and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 7B Instruct 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?

Qwen2.5 7B Instruct has the largest context window at 131,072 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, Qwen2.5 7B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mixtral 8x7B accepts text; Qwen2.5 7B Instruct accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Qwen2.5 7B Instruct is the newest, released Sep 19, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 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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