GPT-4o mini vs Llama-3.2-90B-Vision-Instruct
GPT-4o mini comes out ahead, 49 to 44 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAIGPT-4o mini
49/100- ECI126.5
- Price$0.15 / $0.60
- Context128K
MetaLlama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Add a model
Make it a three-way comparison.
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 sameGPT-4o mini 128,000 · Llama-3.2-90B-Vision-Instruct 128,000 tokens
- Widest inputsGPT-4o miniGPT-4o mini: Text, Images, PDFs · Llama-3.2-90B-Vision-Instruct: Text, Images
- Self-hostingLlama-3.2-90B-Vision-InstructPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | GPT-4o mini | Llama-3.2-90B-Vision-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 47 | 46 |
| Inputs & features | 20% | 70 | 50 |
| Context window | 13% | 24 | 24 |
| Overall | 100% | 49/100 | 44/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-4o miniOpenAI | Llama-3.2-90B-Vision-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 126.5 (best) | 125.5 |
| ECI rank | #148 of 165 (best) | #150 of 165 |
| GPQA DiamondGraduate-level science questions | 37.7% | 41.0% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 0.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.9% (best) | 2.6% |
| 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 window | 128,000 tokens | 128,000 tokens |
| Max output | 16,384 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | OpenLlama 3.2 Community License |
| API model ID | gpt-4o-mini | — |
| API providers | 26 (best) | 1 |
| Released | Jul 18, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Sep 2023 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-4o mini$2.70
- Llama-3.2-90B-Vision-Instruct—
Which should you choose?
Which is better: GPT-4o mini or Llama-3.2-90B-Vision-Instruct?
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, GPT-4o mini or Llama-3.2-90B-Vision-Instruct?
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 GPT-4o mini and Llama-3.2-90B-Vision-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. Both support tool calling for agent workflows.
Which has the bigger context window?
GPT-4o mini and Llama-3.2-90B-Vision-Instruct share the same 128,000-token context window. Maximum output per response: GPT-4o mini up to 16,384, Llama-3.2-90B-Vision-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
GPT-4o mini accepts text, images and PDFs; Llama-3.2-90B-Vision-Instruct accepts text and images. 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: GPT-4o mini Sep 2023, Llama-3.2-90B-Vision-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 Nov 2, 2026.
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