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Comparison · 3 models · Updated Oct 4, 2026

Llama-3.1-70B-Instruct vs GPT-4o vs GPT-4o mini

GPT-4o mini comes out ahead, 56 to 44 and 43 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. OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
    Full specs Remove GPT-4o
  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 GPT-4o (43). It leads on price. GPT-4o wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · GPT-4o mini 126.6 · Llama-3.1-70B-Instruct 125.9
  • Lowest priceGPT-4o miniGPT-4o mini $0.263 · Llama-3.1-70B-Instruct $0.72 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameLlama-3.1-70B-Instruct 128,000 · GPT-4o 128,000 · GPT-4o mini 128,000 tokens
  • Widest inputsGPT-4o and GPT-4o miniLlama-3.1-70B-Instruct: Text · GPT-4o: Text, Images, PDFs · GPT-4o mini: Text, Images, PDFs
  • Self-hostingLlama-3.1-70B-InstructPublishes downloadable weights
How the score is built
MeasureWeightLlama-3.1-70B-InstructGPT-4oGPT-4o mini
CapabilityCapabilities Index (ECI)50%485249
Price25%571977
Inputs & features15%257070
Context window10%242424
Overall100%44/10043/10056/100
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 GPT-4o vs GPT-4o mini specifications side by side
SpecificationLlama-3.1-70B-InstructMetaGPT-4oOpenAIGPT-4o miniOpenAI
Capability
Capabilities Index (ECI)125.9129.0 (best)126.6
ECI rank#136 of 148#129 of 148 (best)#135 of 148
GPQA DiamondGraduate-level science questions44.2%48.9% (best)37.7%
FrontierMath Tiers 1–3Research-level mathematics——0.7%
OTIS Mock AIME 2024–2025Competition mathematics3.6%6.3%6.9% (best)
SimpleQA VerifiedShort factual questions——8.3%
Price per million tokens
Input$0.72$2.50$0.15 (best)
Output$0.72$10.00$0.60 (best)
Cached input—$1.25$0.075 (best)
Blended (3:1)$0.72$4.38$0.263 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 5 providersOfficial OpenAI APIOfficial OpenAI API
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output4,096 tokens16,384 tokens (best)16,384 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryProprietary
API model ID—gpt-4ogpt-4o-mini
API providers51921 (best)
ReleasedJul 23, 2024May 13, 2024Jul 18, 2024
Knowledge cutoffDec 2023Sep 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.

  • Llama-3.1-70B-Instruct$8.64
  • GPT-4o$45.00
  • GPT-4o mini$2.70
04 — Questions

Which should you choose?

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

GPT-4o mini is the better all-round choice, scoring 56/100 against Llama-3.1-70B-Instruct (44) and GPT-4o (43). It leads on price. GPT-4o wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

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

GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Llama-3.1-70B-Instruct costs $0.72 input / $0.72 output per million tokens (median across 5 API providers); 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 $0.263 per million tokens for GPT-4o mini versus $0.72 for Llama-3.1-70B-Instruct (2.7× as much) and $4.38 for GPT-4o (17× as much).

Which scores higher on benchmarks?

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), GPT-4o mini 126.6 (#135 of 148) and Llama-3.1-70B-Instruct 125.9 (#136 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 120.5–128.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Llama-3.1-70B-Instruct 44.2%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — GPT-4o mini 6.9%, GPT-4o 6.3%, Llama-3.1-70B-Instruct 3.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-70B-Instruct, GPT-4o and GPT-4o mini 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, GPT-4o and GPT-4o mini share the same 128,000-token context window. Maximum output per response: Llama-3.1-70B-Instruct up to 4,096, GPT-4o up to 16,384, GPT-4o mini up to 16,384 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

Llama-3.1-70B-Instruct publishes its weights and can be self-hosted; GPT-4o and 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; GPT-4o came out May 13, 2024. Knowledge cutoff: Llama-3.1-70B-Instruct Dec 2023, GPT-4o Sep 2023, 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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