Qwen3-VL 30B-A3B vs Llama-3.2-11B-Vision-Instruct vs Llama 3.1 Nemotron 70B Instruct
Too close to call on our weighted score (Qwen3-VL 30B-A3B 59, Llama-3.2-11B-Vision-Instruct 58, Llama 3.1 Nemotron 70B Instruct 45). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3-VL 30B-A3B
59/100- ECI—
- Price$0.20 / $0.80
- Context131K
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
NVIDIALlama 3.1 Nemotron 70B Instruct
45/100- ECI—
- Price$0.478 / $0.504
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3-VL 30B-A3B 59/100, Llama-3.2-11B-Vision-Instruct 58/100, Llama 3.1 Nemotron 70B Instruct 45/100), so choose by what matters most for your work: Llama-3.2-11B-Vision-Instruct on price and Qwen3-VL 30B-A3B 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 priceLlama-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct $0.275 · Qwen3-VL 30B-A3B $0.35 · Llama 3.1 Nemotron 70B Instruct $0.485 per 1M tokens (3:1 blend)
- Longest contextQwen3-VL 30B-A3BQwen3-VL 30B-A3B 131,072 · Llama-3.2-11B-Vision-Instruct 128,000 · Llama 3.1 Nemotron 70B Instruct 128,000 tokens
- Widest inputsQwen3-VL 30B-A3B and Llama-3.2-11B-Vision-InstructQwen3-VL 30B-A3B: Text, Images · Llama-3.2-11B-Vision-Instruct: Text, Images · Llama 3.1 Nemotron 70B Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3-VL 30B-A3B | Llama-3.2-11B-Vision-Instruct | Llama 3.1 Nemotron 70B Instruct |
|---|---|---|---|---|
| Price | 50% | 72 | 76 | 65 |
| Inputs & features | 30% | 60 | 50 | 25 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 59/100 | 58/100 | 45/100 |
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 | Qwen3-VL 30B-A3BAlibaba (Qwen) | Llama-3.2-11B-Vision-InstructMeta | Llama 3.1 Nemotron 70B InstructNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.197 (best) | $0.478 |
| Output | $0.80 | $0.51 | $0.504 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.35 | $0.275 (best) | $0.485 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 2 providers | Median of 2 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 32,768 tokens (best) | 4,096 tokens | 8,192 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 | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | qwen3-vl-30b-a3b | — | nvidia/llama-3.1-nemotron-70b-instruct |
| API providers | 1 | 2 | 3 (best) |
| Released | Apr 2025 | Sep 25, 2024 | Apr 15, 2025 |
| Knowledge cutoff | Apr 2025 | 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.
- Qwen3-VL 30B-A3B$3.60
- Llama-3.2-11B-Vision-Instruct$2.99
- Llama 3.1 Nemotron 70B Instruct$5.79
Which should you choose?
Which is better: Qwen3-VL 30B-A3B, Llama-3.2-11B-Vision-Instruct or Llama 3.1 Nemotron 70B Instruct?
It is close. Our weighted score puts them within a point (Qwen3-VL 30B-A3B 59/100, Llama-3.2-11B-Vision-Instruct 58/100, Llama 3.1 Nemotron 70B Instruct 45/100), so choose by what matters most for your work: Llama-3.2-11B-Vision-Instruct on price and Qwen3-VL 30B-A3B 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, Qwen3-VL 30B-A3B, Llama-3.2-11B-Vision-Instruct or Llama 3.1 Nemotron 70B Instruct?
Llama-3.2-11B-Vision-Instruct is cheaper at $0.197 input / $0.51 output per million tokens (median across 2 API providers). Qwen3-VL 30B-A3B costs $0.20 input / $0.80 output per million tokens (official Alibaba API price); Llama 3.1 Nemotron 70B Instruct costs $0.478 input / $0.504 output per million tokens (median across 2 API providers; free on Nvidia). 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 $0.35 for Qwen3-VL 30B-A3B (1.3× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-VL 30B-A3B has not been scored yet, Llama-3.2-11B-Vision-Instruct has not been scored yet and Llama 3.1 Nemotron 70B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3-VL 30B-A3B, Llama-3.2-11B-Vision-Instruct and Llama 3.1 Nemotron 70B Instruct 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?
Qwen3-VL 30B-A3B has the largest context window at 131,072 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct and 128,000 for Llama 3.1 Nemotron 70B Instruct. Maximum output per response: Qwen3-VL 30B-A3B up to 32,768, Llama-3.2-11B-Vision-Instruct up to 4,096, Llama 3.1 Nemotron 70B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen3-VL 30B-A3B accepts text and images; Llama-3.2-11B-Vision-Instruct accepts text and images; Llama 3.1 Nemotron 70B Instruct accepts text. Qwen3-VL 30B-A3B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Llama 3.1 Nemotron 70B Instruct is the newest, released Apr 15, 2025. Qwen3-VL 30B-A3B came out Apr 2025; Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Qwen3-VL 30B-A3B Apr 2025, 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.
