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Comparison · 2 models · Updated Nov 2, 2026

Mixtral 8x22B Instruct vs Qwen2.5 7B Instruct

Qwen2.5 7B Instruct comes out ahead, 50 to 34 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Mixtral 8x22B Instruct

    Released Apr 17, 2024

    34/100
    • ECI122.0
    • Price$2.00 / $6.00
    • Context66K
    Full specs Remove Mixtral 8x22B Instruct
  2. Our pick

    Alibaba (Qwen)

    Qwen2.5 7B Instruct

    Released Sep 19, 2024

    50/100
    • ECI118.5
    • Price$0.05 / $0.10
    • 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 50/100 against Mixtral 8x22B Instruct (34). It leads on price and context window. Mixtral 8x22B Instruct wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMixtral 8x22B InstructCapabilities Index (ECI): Mixtral 8x22B Instruct 122.0 · Qwen2.5 7B Instruct 118.5
  • Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Mixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Mixtral 8x22B Instruct 65,536 tokens
  • Widest inputsMixtral 8x22B InstructMixtral 8x22B Instruct: Text, PDFs · 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 8x22B InstructQwen2.5 7B Instruct
CapabilityCapabilities Index (ECI)50%4238
Price25%26100
Inputs & features15%3525
Context window10%1225
Overall100%34/10050/100
02 — Side by side

Every spec in one table

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

Mixtral 8x22B Instruct vs Qwen2.5 7B Instruct specifications side by side
SpecificationMixtral 8x22B InstructMistral AIQwen2.5 7B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)122.0 (best)118.5
ECI rank#155 of 165 (best)#159 of 165
GPQA DiamondGraduate-level science questions34.1%35.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics—2.5%
Price per million tokens
Input$2.00$0.05 (best)
Output$6.00$0.10 (best)
Cached input——
Blended (3:1)$3.00$0.063 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 3 providers
Limits
Context window65,536 tokens131,072 tokens (best)
Max output52,428 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsYesNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenApache 2.0
API model ID——
API providers5 (best)4
ReleasedApr 17, 2024Sep 19, 2024
Knowledge cutoffJan 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.

  • Mixtral 8x22B Instruct$32.00
  • Qwen2.5 7B Instruct$0.70
04 — Questions

Which should you choose?

Which is better: Mixtral 8x22B Instruct or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is the better all-round choice, scoring 50/100 against Mixtral 8x22B Instruct (34). It leads on price and context window. Mixtral 8x22B Instruct wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mixtral 8x22B Instruct or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Mixtral 8x22B Instruct 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 $0.063 per million tokens for Qwen2.5 7B Instruct versus $3.00 for Mixtral 8x22B Instruct (48× as much).

Which scores higher on benchmarks?

Mixtral 8x22B Instruct scores higher on the Capabilities Index (ECI): Mixtral 8x22B Instruct 122.0 (#155 of 165) and Qwen2.5 7B Instruct 118.5 (#159 of 165). The confidence ranges of the top two overlap (115.7–124.3 vs 110.6–121.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 7B Instruct 35.5%, Mixtral 8x22B Instruct 34.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Mixtral 8x22B Instruct and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Mixtral 8x22B 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 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Mixtral 8x22B Instruct up to 52,428, Qwen2.5 7B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mixtral 8x22B Instruct accepts text and PDFs; Qwen2.5 7B Instruct accepts text. Mixtral 8x22B Instruct handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (Apache 2.0), so you can self-host them.

Which is newer?

Qwen2.5 7B Instruct is the newest, released Sep 19, 2024. Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Instruct Jan 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.

05 — Keep comparing

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