Llama-3.2-1B vs Llama-3.2-11B-Vision-Instruct
Llama-3.2-11B-Vision-Instruct comes out ahead, 58 to 55 on our weighted score, though Llama-3.2-1B is 3.2× cheaper per token.
MetaLlama-3.2-1B
55/100- ECI102.0
- Price$0.064 / $0.15
- Context131K
- Our pickMeta
Llama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
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Llama-3.2-11B-Vision-Instruct is our pick
Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 58/100 against Llama-3.2-1B (55). It leads on inputs & features. Llama-3.2-1B wins on price. 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 priceLlama-3.2-1BLlama-3.2-1B $0.085 · Llama-3.2-11B-Vision-Instruct $0.275 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-1BLlama-3.2-1B 131,072 · Llama-3.2-11B-Vision-Instruct 128,000 tokens
- Widest inputsLlama-3.2-11B-Vision-InstructLlama-3.2-1B: Text · Llama-3.2-11B-Vision-Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-1B | Llama-3.2-11B-Vision-Instruct |
|---|---|---|---|
| Price | 50% | 100 | 76 |
| Inputs & features | 30% | 0 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 55/100 | 58/100 |
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-3.2-1BMeta | Llama-3.2-11B-Vision-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 102.0 | — |
| ECI rank | #147 of 148 | — |
| GPQA DiamondGraduate-level science questions | 23.9% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 0.6% | — |
| Price per million tokens | ||
| Input | $0.064 (best) | $0.197 |
| Output | $0.15 (best) | $0.51 |
| Cached input | — | — |
| Blended (3:1) | $0.085 (best) | $0.275 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | No | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenLlama 3.2 Community License | Open |
| API model ID | — | — |
| API providers | 2 | 2 |
| Released | Sep 25, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Dec 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.
- Llama-3.2-1B$0.936
- Llama-3.2-11B-Vision-Instruct$2.99
Which should you choose?
Which is better: Llama-3.2-1B or Llama-3.2-11B-Vision-Instruct?
Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 58/100 against Llama-3.2-1B (55). It leads on inputs & features. Llama-3.2-1B wins on price. 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-3.2-1B or Llama-3.2-11B-Vision-Instruct?
Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 API providers). Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.085 per million tokens for Llama-3.2-1B versus $0.275 for Llama-3.2-11B-Vision-Instruct (3.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Llama-3.2-1B has an ECI of 102.0 and Llama-3.2-11B-Vision-Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-1B and Llama-3.2-11B-Vision-Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-1B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-1B has the largest context window at 131,072 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct. Maximum output per response: Llama-3.2-1B up to 8,192, Llama-3.2-11B-Vision-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-1B accepts text; Llama-3.2-11B-Vision-Instruct accepts text and images. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Llama-3.2-1B is the newest, released Sep 25, 2024. Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-1B Dec 2023, Llama-3.2-11B-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 Oct 4, 2026.
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