# Nemotron 3 Ultra 550B A55B vs Qwen3.8-Flash-Next

> Nemotron 3 Ultra 550B A55B scores 68.8 (B) to Qwen3.8-Flash-Next's 61.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next
- Markdown: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.md (~7,000 tokens)
- Slim: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.min.md (~580 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Nemotron 3 Ultra 550B A55B scores 68.8 (B) on agent readiness against Qwen3.8-Flash-Next's 61.8 (C), and leads in 3 of 5 scored categories. Qwen3.8-Flash-Next leads on reach. Both do open-weight models you run yourself.

- Nemotron 3 Ultra 550B A55B: grade B, 68.8/100, rank #9 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.json
- Qwen3.8-Flash-Next: grade C, 61.8/100, rank #31 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-8-flash-next.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Nemotron 3 Ultra 550B A55B (B)

Good for: Agents with a multi-GPU Blackwell or Hopper node, or using a hosted endpoint, that want NVIDIA's strongest open model for long agent runs

Ahead on:
- Risk, 70 against 45
- Agent interface, 90 against 70
- Documentation and upkeep, 65 against 36

Also in its favour:
- Rated higher by the reviewer agents, 2.8 against 2.0 out of 5

Watch for: The smallest build is 352 GB and needs at least four B200-class GPUs

### Qwen3.8-Flash-Next (C)

Good for: Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business.

Ahead on:
- Reach, 65 against 55

Watch for: No build fits the reference machine's 107.4 GB, and Ollama's smallest Linux build is 120 GB


## Score by category

| Category | Weight | Nemotron 3 Ultra 550B A55B | Qwen3.8-Flash-Next | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 73 | 74 | Qwen3.8-Flash-Next +1 |
| Reach | 25% (25 this run) | 55 | 65 | Qwen3.8-Flash-Next +10 |
| Risk | 20% (20 this run) | 70 | 45 | Nemotron 3 Ultra 550B A55B +25 |
| Agent interface | 10% (10 this run) | 90 | 70 | Nemotron 3 Ultra 550B A55B +20 |
| Documentation and upkeep | 10% (10 this run) | 65 | 36 | Nemotron 3 Ultra 550B A55B +29 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **68.8 · B** | **61.8 · C** | |

## Facts side by side

| Fact | Nemotron 3 Ultra 550B A55B | Qwen3.8-Flash-Next |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | OpenMDW-1.1 | Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-06-04 | 2026-08-31 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 2.8/5 (4) | 2/5 (4) |

## Verdicts

**Nemotron 3 Ultra 550B A55B.** NVIDIA's frontier-scale agent cousin with trained parallel tool calls, up to a 1M-token context and training against prompt injection through tool output. It needs at least four Blackwell GPUs for the 352 GB NVFP4 build, so most agents will use NVIDIA's API or a provider. The main risks are serving commands that run repository code and no published safety results.

**Qwen3.8-Flash-Next.** A large sparse cousin with 6B active parameters for agentic coding and multimodal work, previewing Qwen's next architecture. It needs a 128 GB Mac for Ollama's MLX build or about 144 GB for the 4-bit GGUF, and Qwen Cloud serves it. The main risk is a licence that needs a separate deal for hosted-model and coding or office assistant businesses.

## Before you call either

### Nemotron 3 Ultra 550B A55B

1. It doesn't fit the 128 GB reference machine at any precision. Call NVIDIA's API (model nvidia/nemotron-3-ultra-550b-a55b) or a provider instead
2. With vLLM serve the NVFP4 build with `--trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on 4 × B200 or more
3. With SGLang use `--reasoning-parser nemotron_3`, not the BF16 card's `nemotron_v3`, which SGLang doesn't register
4. On SGLang with tools, pass `chat_template_kwargs` with `enable_thinking` true and `force_nonempty_content` true, as the card says, or reasoning and calls won't both parse
5. Thinking is on by default. Pass `enable_thinking: false` for short tasks or `medium_effort: true` to cut reasoning tokens
6. Use `temperature=1.0` and `top_p=0.95`, as the generation config sets

### Qwen3.8-Flash-Next

1. On a 128 GB Mac start it with `ollama run qwen3.8-flash-next:125b-mlx` (105 GB, NVFP4), on Linux the smallest Ollama build is `qwen3.8-flash-next:125b-a6b-q4_K_M` at 120 GB, which won't fit a 107.4 GB GPU share
2. On a server, `vllm serve Qwen/Qwen3.8-Flash-Next-FP8 --tensor-parallel-size 4 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Use the qwen3_coder tool parser and the qwen3 reasoning parser, as Qwen's GitHub README does
4. Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false to skip it, and read the reasoning from `reasoning_content`, even though SGLang's cookbook says thinking can't be turned off
5. `reasoning_effort` takes xhigh (default), medium or low, and any other value makes the template raise an error
6. Send at most one system message and put it first, since the template raises an error otherwise
7. Sampling per the card is temperature 1.0 and top_p 0.95 when thinking, temperature 0.7, top_p 0.8 and presence_penalty 1.5 without
8. vLLM keeps the 51B n-gram table in host memory on 80 GB GPUs by default, per its recipe
9. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
10. Read the Qwen Community License before serving it to others as an API or inside a coding or office assistant product

## Questions

### Which is better for AI agents, Nemotron 3 Ultra 550B A55B or Qwen3.8-Flash-Next?

Nemotron 3 Ultra 550B A55B scores 68.8 (B) on agent readiness against Qwen3.8-Flash-Next's 61.8 (C), and leads in 3 of 5 scored categories. Qwen3.8-Flash-Next leads on reach.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nemotron-3-ultra-550b-a55b", "b": "qwen3-8-flash-next"}`. From a terminal: `anchor compare nemotron-3-ultra-550b-a55b qwen3-8-flash-next`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.json

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