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Comparison · 3 models · Updated Oct 4, 2026

Mixtral 8x22B vs Llama-3.1-70B-Instruct vs GPT-4o

Too close to call on our weighted score (Llama-3.1-70B-Instruct 44, GPT-4o 43, Mixtral 8x22B 33). The right pick depends on what you value most.

  1. Mistral AI

    Mixtral 8x22B

    Released Apr 17, 2024

    33/100
    • ECI122.0
    • Price$2.00 / $6.00
    • Context64K
    Full specs Remove Mixtral 8x22B

  2. Meta

    Llama-3.1-70B-Instruct

    Released Jul 23, 2024

    44/100
    • ECI125.9
    • Price$0.72 / $0.72
    • Context128K
    Full specs Remove Llama-3.1-70B-Instruct

  3. OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
    Full specs Remove GPT-4o
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Llama-3.1-70B-Instruct 44/100, GPT-4o 43/100, Mixtral 8x22B 33/100), so choose by what matters most for your work: GPT-4o for raw capability and Llama-3.1-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Llama-3.1-70B-Instruct 125.9 · Mixtral 8x22B 122.0
  • Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · Mixtral 8x22B $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextLlama-3.1-70B-Instruct and GPT-4oLlama-3.1-70B-Instruct 128,000 · GPT-4o 128,000 · Mixtral 8x22B 64,000 tokens
  • Widest inputsGPT-4oMixtral 8x22B: Text · Llama-3.1-70B-Instruct: Text · GPT-4o: Text, Images, PDFs
  • Self-hostingMixtral 8x22B and Llama-3.1-70B-InstructPublishes downloadable weights
How the score is built
MeasureWeightMixtral 8x22BLlama-3.1-70B-InstructGPT-4o
CapabilityCapabilities Index (ECI)50%434852
Price25%275719
Inputs & features15%252570
Context window10%122424
Overall100%33/10044/10043/100
02 — Side by side

Every spec in one table

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

Mixtral 8x22B vs Llama-3.1-70B-Instruct vs GPT-4o specifications side by side
SpecificationMixtral 8x22BMistral AILlama-3.1-70B-InstructMetaGPT-4oOpenAI
Capability
Capabilities Index (ECI)122.0125.9129.0 (best)
ECI rank#139 of 148#136 of 148#129 of 148 (best)
GPQA DiamondGraduate-level science questions34.1%44.2%48.9% (best)
OTIS Mock AIME 2024–2025Competition mathematics—3.6%6.3% (best)
Price per million tokens
Input$2.00$0.72 (best)$2.50
Output$6.00$0.72 (best)$10.00
Cached input——$1.25
Blended (3:1)$3.00$0.72 (best)$4.38
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 5 providersOfficial OpenAI API
Limits
Context window64,000 tokens128,000 tokens (best)128,000 tokens (best)
Max output64,000 tokens (best)4,096 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenProprietary
API model IDopen-mixtral-8x22b—gpt-4o
API providers1519 (best)
ReleasedApr 17, 2024Jul 23, 2024May 13, 2024
Knowledge cutoffApr 2024Dec 2023Sep 2023
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$32.00
  • Llama-3.1-70B-Instruct$8.64
  • GPT-4o$45.00
04 — Questions

Which should you choose?

Which is better: Mixtral 8x22B, Llama-3.1-70B-Instruct or GPT-4o?

It is close. Our weighted score puts them within a point (Llama-3.1-70B-Instruct 44/100, GPT-4o 43/100, Mixtral 8x22B 33/100), so choose by what matters most for your work: GPT-4o for raw capability and Llama-3.1-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mixtral 8x22B, Llama-3.1-70B-Instruct or GPT-4o?

Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 5 API providers). Mixtral 8x22B costs $2.00 input / $6.00 output per million tokens (official Mistral API price); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Llama-3.1-70B-Instruct versus $3.00 for Mixtral 8x22B (4.2× as much) and $4.38 for GPT-4o (6.1× as much).

Which scores higher on benchmarks?

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), Llama-3.1-70B-Instruct 125.9 (#136 of 148) and Mixtral 8x22B 122.0 (#139 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 121.0–128.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Llama-3.1-70B-Instruct 44.2%, Mixtral 8x22B 34.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Mixtral 8x22B, Llama-3.1-70B-Instruct and GPT-4o yet, so there is no like-for-like coding score. On overall capability, GPT-4o 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?

Llama-3.1-70B-Instruct and GPT-4o have the largest context windows (128,000 and 128,000 tokens), against 64,000 for Mixtral 8x22B. Maximum output per response: Mixtral 8x22B up to 64,000, Llama-3.1-70B-Instruct up to 4,096, GPT-4o up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Mixtral 8x22B accepts text; Llama-3.1-70B-Instruct accepts text; GPT-4o accepts text, images and PDFs. GPT-4o handles the widest range of inputs.

Are any of these open source?

Mixtral 8x22B and Llama-3.1-70B-Instruct publishes its weights and can be self-hosted; GPT-4o is proprietary.

Which is newer?

Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. GPT-4o came out May 13, 2024; Mixtral 8x22B came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Apr 2024, Llama-3.1-70B-Instruct Dec 2023, GPT-4o Sep 2023.

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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