Qwen3-VL 30B-A3B vs Seed 1.6 Vision vs Llama 3.1 Nemotron 70B Instruct
Seed 1.6 Vision comes out ahead, 63 to 59 and 45 on our weighted score, though Qwen3-VL 30B-A3B is 9% cheaper per token.
Alibaba (Qwen)Qwen3-VL 30B-A3B
59/100- ECI—
- Price$0.20 / $0.80
- Context131K
- Our pick
ByteDance SeedSeed 1.6 Vision
63/100- ECI—
- Price$0.119 / $1.19
- Context256K
NVIDIALlama 3.1 Nemotron 70B Instruct
45/100- ECI—
- Price$0.478 / $0.504
- Context128K
Seed 1.6 Vision is our pick
Seed 1.6 Vision is the better all-round choice, scoring 63/100 against Qwen3-VL 30B-A3B (59) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features and context window. Qwen3-VL 30B-A3B 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 priceQwen3-VL 30B-A3BQwen3-VL 30B-A3B $0.35 · Seed 1.6 Vision $0.386 · Llama 3.1 Nemotron 70B Instruct $0.485 per 1M tokens (3:1 blend)
- Longest contextSeed 1.6 VisionSeed 1.6 Vision 256,000 · Qwen3-VL 30B-A3B 131,072 · Llama 3.1 Nemotron 70B Instruct 128,000 tokens
- Widest inputsQwen3-VL 30B-A3B and Seed 1.6 VisionQwen3-VL 30B-A3B: Text, Images · Seed 1.6 Vision: Text, Images · Llama 3.1 Nemotron 70B Instruct: Text
- Self-hostingQwen3-VL 30B-A3B and Llama 3.1 Nemotron 70B InstructPublishes downloadable weights
| Measure | Weight | Qwen3-VL 30B-A3B | Seed 1.6 Vision | Llama 3.1 Nemotron 70B Instruct |
|---|---|---|---|---|
| Price | 50% | 72 | 69 | 65 |
| Inputs & features | 30% | 60 | 70 | 25 |
| Context window | 20% | 24 | 36 | 24 |
| Overall | 100% | 59/100 | 63/100 | 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) | Seed 1.6 VisionByteDance Seed | Llama 3.1 Nemotron 70B InstructNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.119 (best) | $0.478 |
| Output | $0.80 | $1.19 | $0.504 (best) |
| Cached input | — | $0.024 | — |
| Blended (3:1) | $0.35 (best) | $0.386 | $0.485 |
| Long-context rate | Same rate | Over 32K: $0.178 / $2.37 | Same rate |
| Price source | Official Alibaba API | Official Volcengine Ark API | Median of 2 providers |
| Limits | |||
| Context window | 131,072 tokens | 256,000 tokens (best) | 128,000 tokens |
| Max output | 32,768 tokens (best) | 32,000 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 | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3-vl-30b-a3b | doubao-seed-1-6-vision-250815 | nvidia/llama-3.1-nemotron-70b-instruct |
| API providers | 1 | 2 | 3 (best) |
| Released | Apr 2025 | Aug 15, 2025 | Apr 15, 2025 |
| Knowledge cutoff | Apr 2025 | — | — |
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
- Seed 1.6 Vision$3.56
- Llama 3.1 Nemotron 70B Instruct$5.79
Which should you choose?
Which is better: Qwen3-VL 30B-A3B, Seed 1.6 Vision or Llama 3.1 Nemotron 70B Instruct?
Seed 1.6 Vision is the better all-round choice, scoring 63/100 against Qwen3-VL 30B-A3B (59) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features and context window. Qwen3-VL 30B-A3B 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, Qwen3-VL 30B-A3B, Seed 1.6 Vision or Llama 3.1 Nemotron 70B Instruct?
Qwen3-VL 30B-A3B is cheaper at $0.20 input / $0.80 output per million tokens (official Alibaba API price). Seed 1.6 Vision costs $0.119 input / $1.19 output per million tokens (official Volcengine Ark 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 $0.35 per million tokens for Qwen3-VL 30B-A3B versus $0.386 for Seed 1.6 Vision (1.1× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (1.4× 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, Seed 1.6 Vision 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, Seed 1.6 Vision 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?
Seed 1.6 Vision has the largest context window at 256,000 tokens, against 131,072 for Qwen3-VL 30B-A3B and 128,000 for Llama 3.1 Nemotron 70B Instruct. Maximum output per response: Qwen3-VL 30B-A3B up to 32,768, Seed 1.6 Vision up to 32,000, 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; Seed 1.6 Vision 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?
Qwen3-VL 30B-A3B and Llama 3.1 Nemotron 70B Instruct publishes its weights and can be self-hosted; Seed 1.6 Vision is proprietary.
Which is newer?
Seed 1.6 Vision is the newest, released Aug 15, 2025. Llama 3.1 Nemotron 70B Instruct came out Apr 15, 2025; Qwen3-VL 30B-A3B came out Apr 2025. Knowledge cutoff: Qwen3-VL 30B-A3B Apr 2025.
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.
