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Comparison · 3 models · Updated Nov 2, 2026

Llama-3.1-8B-Instruct vs Mixtral 8x22B Instruct vs Qwen2.5 7B Instruct

Too close to call on our weighted score (Qwen2.5 7B Instruct 50, Llama-3.1-8B-Instruct 49, Mixtral 8x22B Instruct 34). The right pick depends on what you value most.

  1. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    49/100
    • ECI116.4
    • Price$0.06 / $0.08
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct

  2. 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

  3. 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
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100, Mixtral 8x22B Instruct 34/100), so choose by what matters most for your work: Mixtral 8x22B Instruct for raw capability, Qwen2.5 7B Instruct on price and Qwen2.5 7B Instruct for long inputs. 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 · Llama-3.1-8B-Instruct 116.4
  • Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Llama-3.1-8B-Instruct $0.065 · Mixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 · Mixtral 8x22B Instruct 65,536 tokens
  • Widest inputsMixtral 8x22B InstructLlama-3.1-8B-Instruct: Text · Mixtral 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
MeasureWeightLlama-3.1-8B-InstructMixtral 8x22B InstructQwen2.5 7B Instruct
CapabilityCapabilities Index (ECI)50%354238
Price25%10026100
Inputs & features15%253525
Context window10%241225
Overall100%49/10034/10050/100
02 — Side by side

Every spec in one table

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

Llama-3.1-8B-Instruct vs Mixtral 8x22B Instruct vs Qwen2.5 7B Instruct specifications side by side
SpecificationLlama-3.1-8B-InstructMetaMixtral 8x22B InstructMistral AIQwen2.5 7B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)116.4122.0 (best)118.5
ECI rank#162 of 165#155 of 165 (best)#159 of 165
GPQA DiamondGraduate-level science questions27.0%34.1%35.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics1.7%—2.5% (best)
Price per million tokens
Input$0.06$2.00$0.05 (best)
Output$0.08 (best)$6.00$0.10
Cached input———
Blended (3:1)$0.065$3.00$0.063 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 17 providersMedian of 5 providersMedian of 3 providers
Limits
Context window128,000 tokens65,536 tokens131,072 tokens (best)
Max output4,096 tokens52,428 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenApache 2.0
API model ID———
API providers18 (best)54
ReleasedJul 23, 2024Apr 17, 2024Sep 19, 2024
Knowledge cutoffDec 2023Jan 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.

  • Llama-3.1-8B-Instruct$0.76
  • Mixtral 8x22B Instruct$32.00
  • Qwen2.5 7B Instruct$0.70
04 — Questions

Which should you choose?

Which is better: Llama-3.1-8B-Instruct, Mixtral 8x22B Instruct or Qwen2.5 7B Instruct?

It is close. Our weighted score puts them within 1 points (Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100, Mixtral 8x22B Instruct 34/100), so choose by what matters most for your work: Mixtral 8x22B Instruct for raw capability, Qwen2.5 7B Instruct on price and Qwen2.5 7B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-8B-Instruct, 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). Llama-3.1-8B-Instruct costs $0.06 input / $0.08 output per million tokens (median across 17 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 $0.065 for Llama-3.1-8B-Instruct (1× as much) and $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), Qwen2.5 7B Instruct 118.5 (#159 of 165) and Llama-3.1-8B-Instruct 116.4 (#162 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%, Llama-3.1-8B-Instruct 27.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, 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. All three 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 Llama-3.1-8B-Instruct and 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Mixtral 8x22B Instruct up to 52,428, Qwen2.5 7B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-8B-Instruct accepts text; 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, all three 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. Llama-3.1-8B-Instruct came out Jul 23, 2024; Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, 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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