# MiniMax-M3.1-Flash vs Nanbeige4.3-33B

> Nanbeige4.3-33B scores 61 (C) to MiniMax-M3.1-Flash's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b
- Markdown: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b.md (~6,900 tokens)
- Slim: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b.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: 2026-10-25

Nanbeige4.3-33B scores 61 (C) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in every scored category. Both do open-weight models you run yourself.

- MiniMax-M3.1-Flash: grade D, 50.5/100, rank #100 of 111 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m3-1-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.json
- Nanbeige4.3-33B: grade C, 61/100, rank #56 of 111 open-weight models. Markdown https://www.anchorterminal.com/tools/nanbeige-4-3-33b.md · JSON https://www.anchorterminal.com/api/v1/tools/nanbeige-4-3-33b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 3341 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### MiniMax-M3.1-Flash (D)

Good for: Teams with a 4 to 8 GPU server who want an open multimodal agent and coding model with 1M tokens of context and can meet the licence's attribution and notice terms.

Watch for: No released vLLM or SGLang ran it on 24 October 2026; only llama.cpp b11861 from that day did

### Nanbeige4.3-33B (C)

Good for: Agents with about 96 GB of GPU memory, or the 128 GB reference machine, that want an Apache-tagged 33B model for long coding and tool loops and can wait for independent results.

Ahead on:
- Reach, 55 against 40
- Risk, 60 against 35
- Agent interface, 85 against 70
- Documentation and upkeep, 56 against 41

Watch for: No independent benchmark result yet; every agentic number on the card is Nanbeige's own run


## Score by category

| Category | Weight | MiniMax-M3.1-Flash | Nanbeige4.3-33B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 55 | Nanbeige4.3-33B +15 |
| Risk | 20% (20 this run) | 35 | 60 | Nanbeige4.3-33B +25 |
| Agent interface | 10% (10 this run) | 70 | 85 | Nanbeige4.3-33B +15 |
| Documentation and upkeep | 10% (10 this run) | 41 | 56 | Nanbeige4.3-33B +15 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **50.5 · D** | **61 · C** | |

## Facts side by side

| Fact | MiniMax-M3.1-Flash | Nanbeige4.3-33B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | MiniMax | Nanbeige LLM Lab (BOSS Zhipin) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MiniMax Community License (custom; commercial use needs a "Built with MiniMax M3.1-Flash" line and a one-time notice to MiniMax, and MiniMax's written authorisation above $20M yearly revenue) | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-23 | 2026-10-24 |
| 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 | 2.3/5 (4) | none |

## Verdicts

**MiniMax-M3.1-Flash.** A 428B mixture-of-experts model, 23B active, for agent work, coding and computer use, with image and video input, about 1M tokens of context and parallel tool calls. It needs a 4 to 8 GPU server for 250 GB of NVFP4 and MXFP8 weights, and vLLM and SGLang support was pre-release on 24 October 2026. Commercial use needs attribution and notice.

**Nanbeige4.3-33B.** A dense 33B Llama-architecture cousin for long agentic coding and office tasks, with per-request thinking, XML tool calls that stock vLLM and SGLang parse, and 512K of context. It needs about 96 GB at BF16, as Nanbeige ships no quantised build. Its agentic results so far are Nanbeige's own, with no safety results, training data notes or licence file.

## Before you call either

### MiniMax-M3.1-Flash

1. Check the use case first; commercial products must show "Built with MiniMax M3.1-Flash" and notify MiniMax once, or get written authorisation above $20M yearly revenue
2. On 8 H100 or H200 GPUs use vLLM's nightly image vllm/vllm-openai:minimax-m31-flash with --tensor-parallel-size 8 --block-size 128 --kv-cache-dtype fp8 --moe-backend marlin --max-model-len 262144
3. Pass --reasoning-parser minimax_m3 --tool-call-parser minimax_m3 --enable-auto-tool-choice in vLLM, or minimax-m3 for both in SGLang with --trust-remote-code
4. --block-size 128 is mandatory in vLLM, since MSA's sparse block size is 128
5. Set effort per request with chat_template_kwargs reasoning_effort (low, medium, high, xhigh, max); sample at temperature 1.0 and top_p 0.95
6. On Blackwell or MI355X, 4 GPUs serve it with the DSpark draft from dspark/; vLLM's Hopper command leaves DSpark off and turns video input off
7. For GGUF builds by others, use llama.cpp b11861 or later; earlier builds mis-scale the NVFP4 experts and produce garbage
8. Without the hardware, call MiniMax-M3.1-Flash on MiniMax's API (minimax-api), whose thinking defaults to max effort

### Nanbeige4.3-33B

1. Serve with `vllm serve Nanbeige/Nanbeige4.3-33B --enable-auto-tool-choice --reasoning-parser qwen3 --tool-call-parser qwen3_coder`, as the card says, or SGLang with the same two parsers
2. Keep `tool_call_format` at its default `xml`, since qwen3_coder parses that format; the `json` option writes Hermes-style JSON calls, which need a different parser such as vLLM's hermes
3. Pass `chat_template_kwargs` `{"preserve_thinking": true}` for multi-turn tool use and coding, and `{"enable_thinking": false}` to skip reasoning, as the card recommends
4. Use temperature 1.0, top_p 0.95 and up to 65,536 new tokens for agent work, and temperature 0.6 for reasoning and chat, per the card
5. Send your own system prompt, since without one the template injects a Chinese identity line, or a Chinese tool-expert prompt when tools are passed
6. Send one system message at the start only, as the template raises an error for a later one
7. In plain Transformers pass `use_cache=True` to generate, since config.json and generation_config.json set it false; trust_remote_code isn't needed

## Questions

### Which is better for AI agents, MiniMax-M3.1-Flash or Nanbeige4.3-33B?

Nanbeige4.3-33B scores 61 (C) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in every scored category.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-nanbeige-4-3-33b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minimax-m3-1-flash", "b": "nanbeige-4-3-33b"}`. From a terminal: `anchor compare minimax-m3-1-flash nanbeige-4-3-33b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.json and https://www.anchorterminal.com/api/v1/tools/nanbeige-4-3-33b.json

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