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Comparison · 3 models · Updated Oct 4, 2026

Qwen2.5 32B Instruct vs Llama-3.3-70B-Instruct vs Mistral Large 2.1

Too close to call on our weighted score (Llama-3.3-70B-Instruct 46, Qwen2.5 32B Instruct 43, Mistral Large 2.1 38). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen2.5 32B Instruct

    Released Sep 17, 2024

    43/100
    • ECI128.5
    • Price$0.70 / $2.80
    • Context131K
    Full specs Remove Qwen2.5 32B Instruct

  2. Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    46/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct

  3. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 46/100, Qwen2.5 32B Instruct 43/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Llama-3.3-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 32B Instruct and Mistral Large 2.1Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mistral Large 2.1 128.5 · Llama-3.3-70B-Instruct 127.3
  • Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Qwen2.5 32B Instruct $1.23 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 32B Instruct and Mistral Large 2.1Qwen2.5 32B Instruct 131,072 · Mistral Large 2.1 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsSame inputsQwen2.5 32B Instruct: Text · Llama-3.3-70B-Instruct: Text · 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 32B InstructLlama-3.3-70B-InstructMistral Large 2.1
CapabilityCapabilities Index (ECI)50%514951
Price25%466027
Inputs & features15%252525
Context window10%242424
Overall100%43/10046/10038/100
02 — Side by side

Every spec in one table

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

Qwen2.5 32B Instruct vs Llama-3.3-70B-Instruct vs Mistral Large 2.1 specifications side by side
SpecificationQwen2.5 32B InstructAlibaba (Qwen)Llama-3.3-70B-InstructMetaMistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)128.5 (best)127.3128.5 (best)
ECI rank#131 of 148#133 of 148#130 of 148 (best)
GPQA DiamondGraduate-level science questions46.1%47.4%51.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics7.4%5.1%7.8% (best)
Price per million tokens
Input$0.70$0.59 (best)$2.00
Output$2.80$0.724 (best)$6.00
Cached input———
Blended (3:1)$1.23$0.624 (best)$3.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 21 providersOfficial Mistral API
Limits
Context window131,072 tokens (best)128,000 tokens131,072 tokens (best)
Max output8,192 tokens4,096 tokens16,384 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDqwen2-5-32b-instructllama-3.3-70b-instructmistral-large-2411
API providers124 (best)2
ReleasedSep 17, 2024Dec 6, 2024Nov 18, 2024
Knowledge cutoffApr 2024Dec 2023Nov 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 32B Instruct$12.60
  • Llama-3.3-70B-Instruct$7.35
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5 32B Instruct, Llama-3.3-70B-Instruct or Mistral Large 2.1?

It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 46/100, Qwen2.5 32B Instruct 43/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Llama-3.3-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 32B Instruct, Llama-3.3-70B-Instruct or Mistral Large 2.1?

Llama-3.3-70B-Instruct is cheaper at $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). Qwen2.5 32B Instruct costs $0.70 input / $2.80 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 $0.624 per million tokens for Llama-3.3-70B-Instruct versus $1.23 for Qwen2.5 32B Instruct (2× as much) and $3.00 for Mistral Large 2.1 (4.8× 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), Mistral Large 2.1 128.5 (#130 of 148) and Llama-3.3-70B-Instruct 127.3 (#133 of 148). The confidence ranges of the top two overlap (123.5–130.0 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Llama-3.3-70B-Instruct 47.4%, Qwen2.5 32B Instruct 46.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Qwen2.5 32B Instruct 7.4%, Llama-3.3-70B-Instruct 5.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 32B Instruct, Llama-3.3-70B-Instruct and Mistral Large 2.1 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?

Qwen2.5 32B Instruct and Mistral Large 2.1 have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Qwen2.5 32B Instruct up to 8,192, Llama-3.3-70B-Instruct up to 4,096, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 32B Instruct accepts text; Llama-3.3-70B-Instruct accepts text; Mistral Large 2.1 accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Mistral Large 2.1 came out Nov 18, 2024; Qwen2.5 32B Instruct came out Sep 17, 2024. Knowledge cutoff: Qwen2.5 32B Instruct Apr 2024, Llama-3.3-70B-Instruct Dec 2023, 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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