Qwen-VL Plus vs Llama-3.2-11B-Vision-Instruct vs Mistral 7B
Too close to call on our weighted score (Llama-3.2-11B-Vision-Instruct 58, Qwen-VL Plus 57, Mistral 7B 47). The right pick depends on what you value most.
Alibaba (Qwen)Qwen-VL Plus
57/100- ECI—
- Price$0.21 / $0.63
- Context131K
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
Mistral AIMistral 7B
47/100- ECI—
- Price$0.25 / $0.25
- Context8K
Too close to call
It is close. Our weighted score puts them within 1 points (Llama-3.2-11B-Vision-Instruct 58/100, Qwen-VL Plus 57/100, Mistral 7B 47/100), so choose by what matters most for your work: Mistral 7B on price and Qwen-VL Plus for long inputs. 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 priceMistral 7BMistral 7B $0.25 · Llama-3.2-11B-Vision-Instruct $0.275 · Qwen-VL Plus $0.315 per 1M tokens (3:1 blend)
- Longest contextQwen-VL PlusQwen-VL Plus 131,072 · Llama-3.2-11B-Vision-Instruct 128,000 · Mistral 7B 8,000 tokens
- Widest inputsQwen-VL Plus and Llama-3.2-11B-Vision-InstructQwen-VL Plus: Text, Images · Llama-3.2-11B-Vision-Instruct: Text, Images · Mistral 7B: Text
- Self-hostingLlama-3.2-11B-Vision-Instruct and Mistral 7BPublishes downloadable weights
| Measure | Weight | Qwen-VL Plus | Llama-3.2-11B-Vision-Instruct | Mistral 7B |
|---|---|---|---|---|
| Price | 50% | 74 | 76 | 78 |
| Inputs & features | 30% | 50 | 50 | 25 |
| Context window | 20% | 24 | 24 | 0 |
| Overall | 100% | 57/100 | 58/100 | 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-3.2-11B-Vision-InstructMeta | Mistral 7BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.21 | $0.197 (best) | $0.25 |
| Output | $0.63 | $0.51 | $0.25 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.315 | $0.275 | $0.25 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 2 providers | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 8,000 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen-vl-plus | — | open-mistral-7b |
| API providers | 2 (best) | 2 (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-3.2-11B-Vision-Instruct$2.99
- Mistral 7B$3.00
Which should you choose?
Which is better: Qwen-VL Plus, Llama-3.2-11B-Vision-Instruct or Mistral 7B?
It is close. Our weighted score puts them within 1 points (Llama-3.2-11B-Vision-Instruct 58/100, Qwen-VL Plus 57/100, Mistral 7B 47/100), so choose by what matters most for your work: Mistral 7B on price and Qwen-VL Plus for long inputs. 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-3.2-11B-Vision-Instruct or Mistral 7B?
Mistral 7B is cheaper at $0.25 input / $0.25 output per million tokens (official Mistral API price). Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers); 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 $0.25 per million tokens for Mistral 7B versus $0.275 for Llama-3.2-11B-Vision-Instruct (1.1× as much) and $0.315 for Qwen-VL Plus (1.3× 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-3.2-11B-Vision-Instruct 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-3.2-11B-Vision-Instruct and Mistral 7B 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?
Qwen-VL Plus has the largest context window at 131,072 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct and 8,000 for Mistral 7B. Maximum output per response: Qwen-VL Plus up to 8,192, Llama-3.2-11B-Vision-Instruct up to 4,096, Mistral 7B up to 8,000 tokens.
Which can read images, PDFs, audio or video?
Qwen-VL Plus accepts text and images; Llama-3.2-11B-Vision-Instruct accepts text and images; Mistral 7B accepts text. Qwen-VL Plus handles the widest range of inputs.
Are any of these open source?
Llama-3.2-11B-Vision-Instruct and Mistral 7B publishes its weights and can be self-hosted; Qwen-VL Plus is proprietary.
Which is newer?
Llama-3.2-11B-Vision-Instruct 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-3.2-11B-Vision-Instruct 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.
