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Comparison · 3 models · Updated Oct 4, 2026

Llama-3.1-70B-Instruct vs Mixtral 8x7B vs GPT-4o mini

GPT-4o mini comes out ahead, 56 to 44 and 37 on our weighted score, and it is the cheaper option too.

  1. 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

  2. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

    37/100
    • ECI118.5
    • Price$0.70 / $0.70
    • Context32K
    Full specs Remove Mixtral 8x7B
  3. Our pick

    OpenAI

    GPT-4o mini

    Released Jul 18, 2024

    56/100
    • ECI126.6
    • Price$0.15 / $0.60
    • Context128K
    Full specs Remove GPT-4o mini
01 — Verdict

GPT-4o mini is our pick

GPT-4o mini is the better all-round choice, scoring 56/100 against Llama-3.1-70B-Instruct (44) and Mixtral 8x7B (37). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4o miniCapabilities Index (ECI): GPT-4o mini 126.6 · Llama-3.1-70B-Instruct 125.9 · Mixtral 8x7B 118.5
  • Lowest priceGPT-4o miniGPT-4o mini $0.263 · Mixtral 8x7B $0.70 · Llama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend)
  • Longest contextLlama-3.1-70B-Instruct and GPT-4o miniLlama-3.1-70B-Instruct 128,000 · GPT-4o mini 128,000 · Mixtral 8x7B 32,000 tokens
  • Widest inputsGPT-4o miniLlama-3.1-70B-Instruct: Text · Mixtral 8x7B: Text · GPT-4o mini: Text, Images, PDFs
  • Self-hostingLlama-3.1-70B-Instruct and Mixtral 8x7BPublishes downloadable weights
How the score is built
MeasureWeightLlama-3.1-70B-InstructMixtral 8x7BGPT-4o mini
CapabilityCapabilities Index (ECI)50%483849
Price25%575777
Inputs & features15%252570
Context window10%24024
Overall100%44/10037/10056/100
02 — Side by side

Every spec in one table

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

Llama-3.1-70B-Instruct vs Mixtral 8x7B vs GPT-4o mini specifications side by side
SpecificationLlama-3.1-70B-InstructMetaMixtral 8x7BMistral AIGPT-4o miniOpenAI
Capability
Capabilities Index (ECI)125.9118.5126.6 (best)
ECI rank#136 of 148#142 of 148#135 of 148 (best)
GPQA DiamondGraduate-level science questions44.2% (best)30.6%37.7%
FrontierMath Tiers 1–3Research-level mathematics——0.7%
OTIS Mock AIME 2024–2025Competition mathematics3.6%—6.9% (best)
SimpleQA VerifiedShort factual questions——8.3%
Price per million tokens
Input$0.72$0.70$0.15 (best)
Output$0.72$0.70$0.60 (best)
Cached input——$0.075
Blended (3:1)$0.72$0.70$0.263 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 5 providersOfficial Mistral APIOfficial OpenAI API
Limits
Context window128,000 tokens (best)32,000 tokens128,000 tokens (best)
Max output4,096 tokens32,000 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenProprietary
API model ID—open-mixtral-8x7bgpt-4o-mini
API providers5121 (best)
ReleasedJul 23, 2024Dec 11, 2023Jul 18, 2024
Knowledge cutoffDec 2023Jan 2024Sep 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.

  • Llama-3.1-70B-Instruct$8.64
  • Mixtral 8x7B$8.40
  • GPT-4o mini$2.70
04 — Questions

Which should you choose?

Which is better: Llama-3.1-70B-Instruct, Mixtral 8x7B or GPT-4o mini?

GPT-4o mini is the better all-round choice, scoring 56/100 against Llama-3.1-70B-Instruct (44) and Mixtral 8x7B (37). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-70B-Instruct, Mixtral 8x7B or GPT-4o mini?

GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price); Llama-3.1-70B-Instruct costs $0.72 input / $0.72 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT-4o mini versus $0.70 for Mixtral 8x7B (2.7× as much) and $0.72 for Llama-3.1-70B-Instruct (2.7× as much).

Which scores higher on benchmarks?

GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.6 (#135 of 148), Llama-3.1-70B-Instruct 125.9 (#136 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (120.5–128.5 vs 121.0–128.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, GPT-4o mini 37.7%, Mixtral 8x7B 30.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-70B-Instruct, Mixtral 8x7B and GPT-4o mini yet, so there is no like-for-like coding score. On overall capability, GPT-4o mini 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 mini have the largest context windows (128,000 and 128,000 tokens), against 32,000 for Mixtral 8x7B. Maximum output per response: Llama-3.1-70B-Instruct up to 4,096, Mixtral 8x7B up to 32,000, GPT-4o mini up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-70B-Instruct accepts text; Mixtral 8x7B accepts text; GPT-4o mini accepts text, images and PDFs. GPT-4o mini handles the widest range of inputs.

Are any of these open source?

Llama-3.1-70B-Instruct and Mixtral 8x7B publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

Which is newer?

Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. GPT-4o mini came out Jul 18, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Llama-3.1-70B-Instruct Dec 2023, Mixtral 8x7B Jan 2024, GPT-4o mini 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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