Llama-3.2-3B vs Qwen2.5-VL 7B Instruct
Too close to call on our weighted score (Qwen2.5-VL 7B Instruct 51, Llama-3.2-3B 49). The right pick depends on what you value most.
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Alibaba (Qwen)Qwen2.5-VL 7B Instruct
51/100- ECI—
- Price$0.35 / $1.05
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (Qwen2.5-VL 7B Instruct 51/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama-3.2-3B 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-3.2-3BLlama-3.2-3B $0.159 · Qwen2.5-VL 7B Instruct $0.525 per 1M tokens (3:1 blend)
- Longest contextAbout the sameLlama-3.2-3B 131,072 · Qwen2.5-VL 7B Instruct 131,072 tokens
- Widest inputsQwen2.5-VL 7B InstructLlama-3.2-3B: Text · Qwen2.5-VL 7B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-3B | Qwen2.5-VL 7B Instruct |
|---|---|---|---|
| Price | 50% | 88 | 63 |
| Inputs & features | 30% | 0 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 49/100 | 51/100 |
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-3.2-3BMeta | Qwen2.5-VL 7B InstructAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.10 (best) | $0.35 |
| Output | $0.335 (best) | $1.05 |
| Cached input | — | — |
| Blended (3:1) | $0.159 (best) | $0.525 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Alibaba API |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 8,192 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 | — | qwen2-5-vl-7b-instruct |
| API providers | 3 (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-3.2-3B$1.67
- Qwen2.5-VL 7B Instruct$5.60
Which should you choose?
Which is better: Llama-3.2-3B or Qwen2.5-VL 7B Instruct?
It is close. Our weighted score puts them within 3 points (Qwen2.5-VL 7B Instruct 51/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama-3.2-3B 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-3.2-3B or Qwen2.5-VL 7B Instruct?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). Qwen2.5-VL 7B Instruct costs $0.35 input / $1.05 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.159 per million tokens for Llama-3.2-3B versus $0.525 for Qwen2.5-VL 7B Instruct (3.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Llama-3.2-3B has not been scored yet and Qwen2.5-VL 7B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-3B and Qwen2.5-VL 7B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-3B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-3B and Qwen2.5-VL 7B Instruct share the same 131,072-token context window. Maximum output per response: Llama-3.2-3B up to 8,192, Qwen2.5-VL 7B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-3B accepts text; Qwen2.5-VL 7B Instruct accepts text and images. Qwen2.5-VL 7B 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-3.2-3B is the newest, released Sep 25, 2024. Qwen2.5-VL 7B Instruct came out Sep 2024. Knowledge cutoff: Llama-3.2-3B Dec 2023, Qwen2.5-VL 7B 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.
