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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5-VL 7B Instruct vs Mistral Large 2.1

Qwen2.5-VL 7B Instruct comes out ahead, 51 to 26 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen2.5-VL 7B Instruct

    Released Sep 2024

    51/100
    • ECI—
    • Price$0.35 / $1.05
    • Context131K
    Full specs Remove Qwen2.5-VL 7B Instruct

  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    26/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen2.5-VL 7B Instruct is our pick

Qwen2.5-VL 7B Instruct is the better all-round choice, scoring 51/100 against Mistral Large 2.1 (26). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct $0.525 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen2.5-VL 7B Instruct 131,072 · Mistral Large 2.1 131,072 tokens
  • Widest inputsQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct: Text, Images · Mistral Large 2.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5-VL 7B InstructMistral Large 2.1
Price50%6327
Inputs & features30%5025
Context window20%2424
Overall100%51/10026/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Qwen2.5-VL 7B Instruct vs Mistral Large 2.1 specifications side by side
SpecificationQwen2.5-VL 7B InstructAlibaba (Qwen)Mistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)—128.5
ECI rank—#130 of 148
GPQA DiamondGraduate-level science questions—51.3%
OTIS Mock AIME 2024–2025Competition mathematics—7.8%
Price per million tokens
Input$0.35 (best)$2.00
Output$1.05 (best)$6.00
Cached input——
Blended (3:1)$0.525 (best)$3.00
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral API
Limits
Context window131,072 tokens131,072 tokens
Max output8,192 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDqwen2-5-vl-7b-instructmistral-large-2411
API providers12 (best)
ReleasedSep 2024Nov 18, 2024
Knowledge cutoffApr 2024Nov 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-VL 7B Instruct$5.60
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5-VL 7B Instruct or Mistral Large 2.1?

Qwen2.5-VL 7B Instruct is the better all-round choice, scoring 51/100 against Mistral Large 2.1 (26). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Qwen2.5-VL 7B Instruct or Mistral Large 2.1?

Qwen2.5-VL 7B Instruct is cheaper at $0.35 input / $1.05 output per million tokens (official Alibaba API price). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for Qwen2.5-VL 7B Instruct versus $3.00 for Mistral Large 2.1 (5.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen2.5-VL 7B Instruct has not been scored yet and Mistral Large 2.1 has an ECI of 128.5.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5-VL 7B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen2.5-VL 7B Instruct and Mistral Large 2.1 share the same 131,072-token context window. Maximum output per response: Qwen2.5-VL 7B Instruct up to 8,192, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5-VL 7B Instruct accepts text and images; Mistral Large 2.1 accepts text. Qwen2.5-VL 7B Instruct handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5-VL 7B Instruct came out Sep 2024. Knowledge cutoff: Qwen2.5-VL 7B Instruct Apr 2024, Mistral Large 2.1 Nov 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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