Qwen3.5-397B-A17B vs NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 |
|---|---|---|
| Developer | Qwen | NVIDIA |
| Family | Qwen3 5 397b A17b | Nvidia Nemotron 3 Ultra 550b A55b Bf16 |
| Model | Qwen3.5-397B-A17B | NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 |
| Version | Qwen3.5-397B-A17B | NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 |
| Lifecycle | active | active |
| Released | 2026-02-15 | 2026-06-04 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 262,144 | 262,144 |
| Total parameters | 403,397,928,944 | 560,524,578,816 |
| Active parameters | 17,000,000,000 | 55,000,000,000 |
| License | apache-2.0 | other |
| Open weights | Yes | Yes |
| API available | Yes | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Openrouter (Standard) | Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
16 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Qwen3.5-397B-A17B Capabilities
NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Qwen3.5-397B-A17B vs NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 FAQs
Is Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5-397B-A17B and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
Qwen3.5-397B-A17B is $0.39 and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is $0.50 per million tokens, so Qwen3.5-397B-A17B is cheaper on this metric. Qwen3.5-397B-A17B is $2.34 and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is $2.20 per million tokens, so NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is cheaper on this metric.
Which has a larger context window, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
Neither model has a larger sourced context window in this comparison. Qwen3.5-397B-A17B is 262,144 and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is 262,144.
Which performs better in benchmarks, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5-397B-A17B is open weight; NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is open weight.
Can Qwen3.5-397B-A17B and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 understand images?+
Qwen3.5-397B-A17B is documented with image input; NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
Neither has a larger sourced maximum output. Qwen3.5-397B-A17B is — and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 is —.
Do Qwen3.5-397B-A17B and NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 support reasoning and tool use?+
Qwen3.5-397B-A17B: reasoning, tool calling, and image input. NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
Qwen3.5-397B-A17B has 2 sourced provider routes; NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 has 1, so Qwen3.5-397B-A17B has broader tracked availability.
Which offers better value, Qwen3.5-397B-A17B or NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.