Qwen3 Omni 30B A3B Thinking vs Llama 3.3 Nemotron Super 49B v1.5
Qwen3 Omni 30B A3B Thinking comes out ahead, 59 to 48 on our weighted score, though Llama 3.3 Nemotron Super 49B v1.5 is 7% cheaper per token.
- Our pick
Alibaba (Qwen)Qwen3 Omni 30B A3B Thinking
59/100- ECI—
- Price$0.25 / $0.97
- Context66K
NVIDIALlama 3.3 Nemotron Super 49B v1.5
48/100- ECI—
- Price$0.40 / $0.40
- Context131K
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Make it a three-way comparison.
Qwen3 Omni 30B A3B Thinking is our pick
Qwen3 Omni 30B A3B Thinking is the better all-round choice, scoring 59/100 against Llama 3.3 Nemotron Super 49B v1.5 (48). It leads on inputs & features. Llama 3.3 Nemotron Super 49B v1.5 wins on context window. 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 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 $0.40 · Qwen3 Omni 30B A3B Thinking $0.43 per 1M tokens (3:1 blend)
- Longest contextLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 131,072 · Qwen3 Omni 30B A3B Thinking 65,536 tokens
- Widest inputsQwen3 Omni 30B A3B ThinkingQwen3 Omni 30B A3B Thinking: Text, Images, Audio, Video · Llama 3.3 Nemotron Super 49B v1.5: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 Omni 30B A3B Thinking | Llama 3.3 Nemotron Super 49B v1.5 |
|---|---|---|---|
| Price | 50% | 64 | 66 |
| Inputs & features | 30% | 80 | 35 |
| Context window | 20% | 12 | 25 |
| Overall | 100% | 59/100 | 48/100 |
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 Omni 30B A3B ThinkingAlibaba (Qwen) | Llama 3.3 Nemotron Super 49B v1.5NVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.25 (best) | $0.40 |
| Output | $0.97 | $0.40 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.43 | $0.40 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers |
| Limits | ||
| Context window | 65,536 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache-2.0 | Open |
| API model ID | — | — |
| API providers | 1 | 1 |
| Released | Sep 22, 2025 | Jul 25, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 Omni 30B A3B Thinking$4.44
- Llama 3.3 Nemotron Super 49B v1.5$4.80
Which should you choose?
Which is better: Qwen3 Omni 30B A3B Thinking or Llama 3.3 Nemotron Super 49B v1.5?
Qwen3 Omni 30B A3B Thinking is the better all-round choice, scoring 59/100 against Llama 3.3 Nemotron Super 49B v1.5 (48). It leads on inputs & features. Llama 3.3 Nemotron Super 49B v1.5 wins on context window. 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 Omni 30B A3B Thinking or Llama 3.3 Nemotron Super 49B v1.5?
Llama 3.3 Nemotron Super 49B v1.5 is cheaper at $0.40 input / $0.40 output per million tokens (median across 1 API provider). Qwen3 Omni 30B A3B Thinking costs $0.25 input / $0.97 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Llama 3.3 Nemotron Super 49B v1.5 versus $0.43 for Qwen3 Omni 30B A3B Thinking (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen3 Omni 30B A3B Thinking has not been scored yet and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 Omni 30B A3B Thinking and Llama 3.3 Nemotron Super 49B v1.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama 3.3 Nemotron Super 49B v1.5 has the largest context window at 131,072 tokens, against 65,536 for Qwen3 Omni 30B A3B Thinking. Maximum output per response: Qwen3 Omni 30B A3B Thinking up to 16,384, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3 Omni 30B A3B Thinking accepts text, images, audio and video; Llama 3.3 Nemotron Super 49B v1.5 accepts text. Qwen3 Omni 30B A3B Thinking handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Qwen3 Omni 30B A3B Thinking is the newest, released Sep 22, 2025. Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 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 Nov 2, 2026.
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