Llama-3.1-70B-Instruct vs Llama-3.2-11B-Vision-Instruct vs GPT-4o mini
GPT-4o mini comes out ahead, 64 to 58 and 41 on our weighted score, and it is the cheaper option too.
MetaLlama-3.1-70B-Instruct
41/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
- Meta
Llama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
- Our pick
OpenAIGPT-4o mini
64/100- ECI126.6
- Price$0.15 / $0.60
- Context128K
GPT-4o mini is our pick
GPT-4o mini is the better all-round choice, scoring 64/100 against Llama-3.2-11B-Vision-Instruct (58) and Llama-3.1-70B-Instruct (41). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGPT-4o miniGPT-4o mini $0.263 · Llama-3.2-11B-Vision-Instruct $0.275 · Llama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend)
- Longest contextAbout the sameLlama-3.1-70B-Instruct 128,000 · Llama-3.2-11B-Vision-Instruct 128,000 · GPT-4o mini 128,000 tokens
- Widest inputsGPT-4o miniLlama-3.1-70B-Instruct: Text · Llama-3.2-11B-Vision-Instruct: Text, Images · GPT-4o mini: Text, Images, PDFs
- Self-hostingLlama-3.1-70B-Instruct and Llama-3.2-11B-Vision-InstructPublishes downloadable weights
| Measure | Weight | Llama-3.1-70B-Instruct | Llama-3.2-11B-Vision-Instruct | GPT-4o mini |
|---|---|---|---|---|
| Price | 50% | 57 | 76 | 77 |
| Inputs & features | 30% | 25 | 50 | 70 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 41/100 | 58/100 | 64/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.1-70B-InstructMeta | Llama-3.2-11B-Vision-InstructMeta | GPT-4o miniOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 125.9 | — | 126.6 (best) |
| ECI rank | #136 of 148 | — | #135 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 44.2% (best) | — | 37.7% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 0.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 3.6% | — | 6.9% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 8.3% |
| Price per million tokens | |||
| Input | $0.72 | $0.197 | $0.15 (best) |
| Output | $0.72 | $0.51 (best) | $0.60 |
| Cached input | — | — | $0.075 |
| Blended (3:1) | $0.72 | $0.275 | $0.263 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 2 providers | Official OpenAI API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 4,096 tokens | 16,384 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | — | gpt-4o-mini |
| API providers | 5 | 2 | 21 (best) |
| Released | Jul 23, 2024 | Sep 25, 2024 | Jul 18, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 2023 | Sep 2023 |
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
- Llama-3.2-11B-Vision-Instruct$2.99
- GPT-4o mini$2.70
Which should you choose?
Which is better: Llama-3.1-70B-Instruct, Llama-3.2-11B-Vision-Instruct or GPT-4o mini?
GPT-4o mini is the better all-round choice, scoring 64/100 against Llama-3.2-11B-Vision-Instruct (58) and Llama-3.1-70B-Instruct (41). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Llama-3.1-70B-Instruct, Llama-3.2-11B-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). Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers); 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 $0.275 for Llama-3.2-11B-Vision-Instruct (1× as much) and $0.72 for Llama-3.1-70B-Instruct (2.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.1-70B-Instruct has an ECI of 125.9, Llama-3.2-11B-Vision-Instruct has not been scored yet and GPT-4o mini has an ECI of 126.6.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.1-70B-Instruct, Llama-3.2-11B-Vision-Instruct and GPT-4o mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Llama-3.1-70B-Instruct, Llama-3.2-11B-Vision-Instruct 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, Llama-3.2-11B-Vision-Instruct up to 4,096, GPT-4o mini up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Llama-3.1-70B-Instruct accepts text; Llama-3.2-11B-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-3.1-70B-Instruct and Llama-3.2-11B-Vision-Instruct publishes its weights and can be self-hosted; GPT-4o mini is proprietary.
Which is newer?
Llama-3.2-11B-Vision-Instruct is the newest, released Sep 25, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024; GPT-4o mini came out Jul 18, 2024. Knowledge cutoff: Llama-3.1-70B-Instruct Dec 2023, Llama-3.2-11B-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 Oct 4, 2026.
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