Llama-3.2-11B-Vision-Instruct vs Qwen2.5-VL 72B Instruct
Llama-3.2-11B-Vision-Instruct comes out ahead, 58 to 30 on our weighted score, and it is the cheaper option too.
- Our pick
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
Alibaba (Qwen)Qwen2.5-VL 72B Instruct
30/100- ECI—
- Price$2.80 / $8.40
- Context131K
Add a model
Make it a three-way comparison.
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 Qwen2.5-VL 72B Instruct (30). It leads 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-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct $0.275 · Qwen2.5-VL 72B Instruct $4.20 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-VL 72B InstructQwen2.5-VL 72B Instruct 131,072 · Llama-3.2-11B-Vision-Instruct 128,000 tokens
- Widest inputsSame inputsLlama-3.2-11B-Vision-Instruct: Text, Images · Qwen2.5-VL 72B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-11B-Vision-Instruct | Qwen2.5-VL 72B Instruct |
|---|---|---|---|
| Price | 50% | 76 | 20 |
| Inputs & features | 30% | 50 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 58/100 | 30/100 |
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-3.2-11B-Vision-InstructMeta | Qwen2.5-VL 72B InstructAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.197 (best) | $2.80 |
| Output | $0.51 (best) | $8.40 |
| Cached input | — | — |
| Blended (3:1) | $0.275 (best) | $4.20 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Alibaba API |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | qwen2-5-vl-72b-instruct |
| API providers | 2 (best) | 1 |
| Released | Sep 25, 2024 | Sep 2024 |
| Knowledge cutoff | Dec 2023 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.2-11B-Vision-Instruct$2.99
- Qwen2.5-VL 72B Instruct$44.80
Which should you choose?
Which is better: Llama-3.2-11B-Vision-Instruct or Qwen2.5-VL 72B Instruct?
Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 58/100 against Qwen2.5-VL 72B Instruct (30). It leads 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-3.2-11B-Vision-Instruct or Qwen2.5-VL 72B Instruct?
Llama-3.2-11B-Vision-Instruct is cheaper at $0.197 input / $0.51 output per million tokens (median across 2 API providers). Qwen2.5-VL 72B Instruct costs $2.80 input / $8.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.275 per million tokens for Llama-3.2-11B-Vision-Instruct versus $4.20 for Qwen2.5-VL 72B Instruct (15× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Llama-3.2-11B-Vision-Instruct has not been scored yet and Qwen2.5-VL 72B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-11B-Vision-Instruct and Qwen2.5-VL 72B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen2.5-VL 72B Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct. Maximum output per response: Llama-3.2-11B-Vision-Instruct up to 4,096, Qwen2.5-VL 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-11B-Vision-Instruct accepts text and images; Qwen2.5-VL 72B Instruct accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Llama-3.2-11B-Vision-Instruct is the newest, released Sep 25, 2024. Qwen2.5-VL 72B Instruct came out Sep 2024. Knowledge cutoff: Llama-3.2-11B-Vision-Instruct Dec 2023, Qwen2.5-VL 72B Instruct Apr 2024.
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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