Qwen-VL Plus vs Llama-3.2-3B vs Mistral 7B
Qwen-VL Plus comes out ahead, 57 to 49 and 47 on our weighted score, though Llama-3.2-3B is 2× cheaper per token.
- Our pick
Alibaba (Qwen)Qwen-VL Plus
57/100- ECI—
- Price$0.21 / $0.63
- Context131K
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Mistral AIMistral 7B
47/100- ECI—
- Price$0.25 / $0.25
- Context8K
Qwen-VL Plus is our pick
Qwen-VL Plus is the better all-round choice, scoring 57/100 against Llama-3.2-3B (49) and Mistral 7B (47). It leads on inputs & features. Llama-3.2-3B 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-3.2-3BLlama-3.2-3B $0.159 · Mistral 7B $0.25 · Qwen-VL Plus $0.315 per 1M tokens (3:1 blend)
- Longest contextQwen-VL Plus and Llama-3.2-3BQwen-VL Plus 131,072 · Llama-3.2-3B 131,072 · Mistral 7B 8,000 tokens
- Widest inputsQwen-VL PlusQwen-VL Plus: Text, Images · Llama-3.2-3B: Text · Mistral 7B: Text
- Self-hostingLlama-3.2-3B and Mistral 7BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Qwen-VL Plus | Llama-3.2-3B | Mistral 7B |
|---|---|---|---|---|
| Price | 50% | 74 | 88 | 78 |
| Inputs & features | 30% | 50 | 0 | 25 |
| Context window | 20% | 24 | 24 | 0 |
| Overall | 100% | 57/100 | 49/100 | 47/100 |
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 | Qwen-VL PlusAlibaba (Qwen) | Llama-3.2-3BMeta | Mistral 7BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.21 | $0.10 (best) | $0.25 |
| Output | $0.63 | $0.335 | $0.25 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.315 | $0.159 (best) | $0.25 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 3 providers | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens (best) | 131,072 tokens (best) | 8,000 tokens |
| Max output | 8,192 tokens (best) | 8,192 tokens (best) | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenLlama 3.2 Community License | Open |
| API model ID | qwen-vl-plus | — | open-mistral-7b |
| API providers | 2 | 3 (best) | 1 |
| Released | Jan 25, 2024 | Sep 25, 2024 | Sep 27, 2023 |
| Knowledge cutoff | Apr 2024 | 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.
- Qwen-VL Plus$3.36
- Llama-3.2-3B$1.67
- Mistral 7B$3.00
Which should you choose?
Which is better: Qwen-VL Plus, Llama-3.2-3B or Mistral 7B?
Qwen-VL Plus is the better all-round choice, scoring 57/100 against Llama-3.2-3B (49) and Mistral 7B (47). It leads on inputs & features. Llama-3.2-3B 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, Qwen-VL Plus, Llama-3.2-3B or Mistral 7B?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). Mistral 7B costs $0.25 input / $0.25 output per million tokens (official Mistral API price); Qwen-VL Plus costs $0.21 input / $0.63 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 $0.25 for Mistral 7B (1.6× as much) and $0.315 for Qwen-VL Plus (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen-VL Plus has not been scored yet, Llama-3.2-3B has not been scored yet and Mistral 7B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen-VL Plus, Llama-3.2-3B and Mistral 7B 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?
Qwen-VL Plus and Llama-3.2-3B have the largest context windows (131,072 and 131,072 tokens), against 8,000 for Mistral 7B. Maximum output per response: Qwen-VL Plus up to 8,192, Llama-3.2-3B up to 8,192, Mistral 7B up to 8,000 tokens.
Which can read images, PDFs, audio or video?
Qwen-VL Plus accepts text and images; Llama-3.2-3B accepts text; Mistral 7B accepts text. Qwen-VL Plus handles the widest range of inputs.
Are any of these open source?
Llama-3.2-3B and Mistral 7B publishes its weights (Llama 3.2 Community License) and can be self-hosted; Qwen-VL Plus is proprietary.
Which is newer?
Llama-3.2-3B is the newest, released Sep 25, 2024. Qwen-VL Plus came out Jan 25, 2024; Mistral 7B came out Sep 27, 2023. Knowledge cutoff: Qwen-VL Plus Apr 2024, Llama-3.2-3B Dec 2023, Mistral 7B 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.
