ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Mistral Nemo vs GPT-4o mini vs Llama-3.1-8B-Instruct

GPT-4o mini comes out ahead, 56 to 48 and 46 on our weighted score, though Mistral Nemo is 43% cheaper per token.

  1. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo
  2. 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

  3. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    46/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct
01 — Verdict

GPT-4o mini is our pick

GPT-4o mini is the better all-round choice, scoring 56/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability 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 · Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 · GPT-4o mini $0.263 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameMistral Nemo 128,000 · GPT-4o mini 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
  • Widest inputsGPT-4o miniMistral Nemo: Text · GPT-4o mini: Text, Images, PDFs · Llama-3.1-8B-Instruct: Text
  • Self-hostingMistral Nemo and Llama-3.1-8B-InstructPublishes downloadable weights
How the score is built
MeasureWeightMistral NemoGPT-4o miniLlama-3.1-8B-Instruct
CapabilityCapabilities Index (ECI)50%394936
Price25%897788
Inputs & features15%257025
Context window10%242424
Overall100%48/10056/10046/100
02 — Side by side

Every spec in one table

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

Mistral Nemo vs GPT-4o mini vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMistral NemoMistral AIGPT-4o miniOpenAILlama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)118.7126.6 (best)116.6
ECI rank#140 of 148#135 of 148 (best)#145 of 148
GPQA DiamondGraduate-level science questions29.9%37.7% (best)27.0%
FrontierMath Tiers 1–3Research-level mathematics—0.7%—
OTIS Mock AIME 2024–2025Competition mathematics—6.9% (best)1.7%
SimpleQA VerifiedShort factual questions—8.3%—
Price per million tokens
Input$0.15 (best)$0.15 (best)$0.152
Output$0.15 (best)$0.60$0.167
Cached input—$0.075—
Blended (3:1)$0.15 (best)$0.263$0.156
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial OpenAI APIMedian of 9 providers
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output128,000 tokens (best)16,384 tokens4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpen
API model IDmistral-nemogpt-4o-mini—
API providers521 (best)9
ReleasedJul 1, 2024Jul 18, 2024Jul 23, 2024
Knowledge cutoffJul 2024Sep 2023Dec 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.

  • Mistral Nemo$1.80
  • GPT-4o mini$2.70
  • Llama-3.1-8B-Instruct$1.85
04 — Questions

Which should you choose?

Which is better: Mistral Nemo, GPT-4o mini or Llama-3.1-8B-Instruct?

GPT-4o mini is the better all-round choice, scoring 56/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Nemo, GPT-4o mini or Llama-3.1-8B-Instruct?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); GPT-4o mini costs $0.15 input / $0.60 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Nemo versus $0.156 for Llama-3.1-8B-Instruct (1× as much) and $0.263 for GPT-4o mini (1.8× 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), Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (120.5–128.5 vs 111.3–121.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o mini 37.7%, Mistral Nemo 29.9%, Llama-3.1-8B-Instruct 27.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Nemo, GPT-4o mini and Llama-3.1-8B-Instruct 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?

Mistral Nemo, GPT-4o mini and Llama-3.1-8B-Instruct share the same 128,000-token context window. Maximum output per response: Mistral Nemo up to 128,000, GPT-4o mini up to 16,384, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

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

Which is newer?

Llama-3.1-8B-Instruct is the newest, released Jul 23, 2024. GPT-4o mini came out Jul 18, 2024; Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 2024, GPT-4o mini Sep 2023, Llama-3.1-8B-Instruct Dec 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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