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Comparison · 2 models · Updated Nov 2, 2026

Llama-3.2-90B-Vision-Instruct vs GPT-4o mini

GPT-4o mini comes out ahead, 49 to 44 on our weighted score, and it is the cheaper option too.

  1. Meta

    Llama-3.2-90B-Vision-Instruct

    Released Sep 25, 2024

    44/100
    • ECI125.5
    • Price—
    • Context128K
    Full specs Remove Llama-3.2-90B-Vision-Instruct
  2. Our pick

    OpenAI

    GPT-4o mini

    Released Jul 18, 2024

    49/100
    • ECI126.5
    • Price$0.15 / $0.60
    • Context128K
    Full specs Remove GPT-4o mini

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-4o mini is our pick

GPT-4o mini is the better all-round choice, scoring 49/100 against Llama-3.2-90B-Vision-Instruct (44). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityGPT-4o miniCapabilities Index (ECI): GPT-4o mini 126.5 · Llama-3.2-90B-Vision-Instruct 125.5
  • Lowest priceGPT-4o miniGPT-4o mini $0.263 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
  • Longest contextAbout the sameLlama-3.2-90B-Vision-Instruct 128,000 · GPT-4o mini 128,000 tokens
  • Widest inputsGPT-4o miniLlama-3.2-90B-Vision-Instruct: Text, Images · GPT-4o mini: Text, Images, PDFs
  • Self-hostingLlama-3.2-90B-Vision-InstructPublishes downloadable weights (Llama 3.2 Community License)
How the score is built
MeasureWeightLlama-3.2-90B-Vision-InstructGPT-4o mini
CapabilityCapabilities Index (ECI)67%4647
Inputs & features20%5070
Context window13%2424
Overall100%44/10049/100

Left out because at least one model lacks the data: price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Llama-3.2-90B-Vision-Instruct vs GPT-4o mini specifications side by side
SpecificationLlama-3.2-90B-Vision-InstructMetaGPT-4o miniOpenAI
Capability
Capabilities Index (ECI)125.5126.5 (best)
ECI rank#150 of 165#148 of 165 (best)
GPQA DiamondGraduate-level science questions41.0% (best)37.7%
FrontierMath Tiers 1–3Research-level mathematics—0.7%
OTIS Mock AIME 2024–2025Competition mathematics2.6%6.9% (best)
SimpleQA VerifiedShort factual questions—8.3%
Price per million tokens
Input—$0.15
Output—$0.60
Cached input—$0.075
Blended (3:1)—$0.263
Long-context rate—Same rate
Price source—Official OpenAI API
Limits
Context window128,000 tokens128,000 tokens
Max output4,096 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenLlama 3.2 Community LicenseProprietary
API model ID—gpt-4o-mini
API providers126 (best)
ReleasedSep 25, 2024Jul 18, 2024
Knowledge cutoffDec 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-3.2-90B-Vision-Instruct—
  • GPT-4o mini$2.70
04 — Questions

Which should you choose?

Which is better: Llama-3.2-90B-Vision-Instruct or GPT-4o mini?

GPT-4o mini is the better all-round choice, scoring 49/100 against Llama-3.2-90B-Vision-Instruct (44). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, Llama-3.2-90B-Vision-Instruct or GPT-4o mini?

GPT-4o mini is cheaper at $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 $0.263 per million tokens for GPT-4o mini versus . Llama-3.2-90B-Vision-Instruct has no published per-token price.

Which scores higher on benchmarks?

GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.5 (#148 of 165) and Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165). The confidence ranges of the top two overlap (120.5–128.6 vs 120.3–127.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.2-90B-Vision-Instruct 41.0%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — GPT-4o mini 6.9%, Llama-3.2-90B-Vision-Instruct 2.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct 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. Both support tool calling for agent workflows.

Which has the bigger context window?

Llama-3.2-90B-Vision-Instruct and GPT-4o mini share the same 128,000-token context window. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, GPT-4o mini up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Llama-3.2-90B-Vision-Instruct accepts text and images; GPT-4o mini accepts text, images and PDFs. GPT-4o mini handles the widest range of inputs.

Are any of these open source?

Llama-3.2-90B-Vision-Instruct publishes its weights (Llama 3.2 Community License) and can be self-hosted; GPT-4o mini is proprietary.

Which is newer?

Llama-3.2-90B-Vision-Instruct is the newest, released Sep 25, 2024. GPT-4o mini came out Jul 18, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 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 Nov 2, 2026.

05 — Keep comparing

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