ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 7B Instruct vs Mistral Nemo

Mistral Nemo comes out ahead, 48 to 44 on our weighted score, and it is the cheaper option too.

  1. 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
  2. Our pick

    Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Nemo is our pick

Mistral Nemo is the better all-round choice, scoring 48/100 against Qwen2.5 7B Instruct (44). It leads on price. 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
  • Lowest priceMistral NemoMistral Nemo $0.15 · Qwen2.5 7B Instruct $0.306 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Mistral Nemo 128,000 tokens
  • Widest inputsSame inputsQwen2.5 7B Instruct: Text · Mistral Nemo: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5 7B InstructMistral Nemo
CapabilityCapabilities Index (ECI)50%3839
Price25%7489
Inputs & features15%2525
Context window10%2424
Overall100%44/10048/100
02 — Side by side

Every spec in one table

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

Qwen2.5 7B Instruct vs Mistral Nemo specifications side by side
SpecificationQwen2.5 7B InstructAlibaba (Qwen)Mistral NemoMistral AI
Capability
Capabilities Index (ECI)118.5118.7 (best)
ECI rank#141 of 148#140 of 148 (best)
GPQA DiamondGraduate-level science questions35.5% (best)29.9%
OTIS Mock AIME 2024–2025Competition mathematics2.5%—
Price per million tokens
Input$0.175$0.15 (best)
Output$0.70$0.15 (best)
Cached input——
Blended (3:1)$0.306$0.15 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral API
Limits
Context window131,072 tokens (best)128,000 tokens
Max output8,192 tokens128,000 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDqwen2-5-7b-instructmistral-nemo
API providers15 (best)
ReleasedSep 19, 2024Jul 1, 2024
Knowledge cutoffApr 2024Jul 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.

  • Qwen2.5 7B Instruct$3.15
  • Mistral Nemo$1.80
04 — Questions

Which should you choose?

Which is better: Qwen2.5 7B Instruct or Mistral Nemo?

Mistral Nemo is the better all-round choice, scoring 48/100 against Qwen2.5 7B Instruct (44). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

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

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). 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).

Which scores higher on benchmarks?

Mistral Nemo scores higher on the Capabilities Index (ECI): Mistral Nemo 118.7 (#140 of 148) and Qwen2.5 7B Instruct 118.5 (#141 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 — Qwen2.5 7B Instruct 35.5%, Mistral Nemo 29.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 7B Instruct and Mistral Nemo 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. 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 128,000 for Mistral Nemo. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Mistral Nemo up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 7B Instruct accepts text; Mistral Nemo 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. Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Qwen2.5 7B Instruct Apr 2024, Mistral Nemo Jul 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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