# MiniMax-M2.5 vs Qwen3-4B-Instruct-2507

> MiniMax-M2.5 scores 57.5 (C) to Qwen3-4B-Instruct-2507's 55.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507
- Markdown: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.md (~6,400 tokens)
- Slim: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.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

MiniMax-M2.5 scores 57.5 (C) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 1 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach and risk. Both do open-weight models you run yourself.

- MiniMax-M2.5: grade C, 57.5/100, rank #71 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json
- Qwen3-4B-Instruct-2507: grade C, 55.7/100, rank #77 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.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

### MiniMax-M2.5 (C)

Good for: Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy

Ahead on:
- Capability, 73 against 31

Watch for: 230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine

### Qwen3-4B-Instruct-2507 (C)

Good for: Agents that want a capable small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context.

Ahead on:
- Reach, 95 against 65
- Risk, 55 against 30

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 1.8 out of 5

Watch for: No safety results, prompt-injection guidance or security contact


## Score by category

| Category | Weight | MiniMax-M2.5 | Qwen3-4B-Instruct-2507 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 73 | 31 | MiniMax-M2.5 +42 |
| Reach | 25% (25 this run) | 65 | 95 | Qwen3-4B-Instruct-2507 +30 |
| Risk | 20% (20 this run) | 30 | 55 | Qwen3-4B-Instruct-2507 +25 |
| Agent interface | 10% (10 this run) | 75 | 75 | even |
| Documentation and upkeep | 10% (10 this run) | 22 | 26 | Qwen3-4B-Instruct-2507 +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **57.5 · C** | **55.7 · C** | |

## Facts side by side

| Fact | MiniMax-M2.5 | Qwen3-4B-Instruct-2507 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | MiniMax | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MiniMax Model License (model) and modified MIT (code) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-02-12 | 2025-09-17 |
| 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 | 1.8/5 (4) | 3/5 (4) |

## Verdicts

**MiniMax-M2.5.** MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.

**Qwen3-4B-Instruct-2507.** A small, fast cousin for instruction following, short tool-calling jobs and long documents on modest hardware, with no thinking step. It runs in about 3 GB at 4 bits on every common runtime, and two providers host it. The main risk is neglect, with no file changes in over a year, no answers from Alibaba and no safety results.

## Before you call either

### MiniMax-M2.5

1. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think
2. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code
3. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache
4. On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory
5. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends
6. Budget output tokens for thinking on every turn, since the template always opens a think block
7. Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy
8. Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026

### Qwen3-4B-Instruct-2507

1. Quickest start is `ollama run qwen3:4b-instruct`, 2.5 GB. Plain `qwen3:4b` is the Thinking-2507 edition, not this one
2. On our reference machine use BF16 with `vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes`
3. Use the hermes parser in vLLM or qwen25 in SGLang, the template emits JSON inside tool_call tags
4. Don't pass enable_thinking, this edition never thinks and the card says the flag isn't needed
5. Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and min_p 0, with presence_penalty up to 2 against repetition
6. Drop the context to 32,768 tokens if memory runs out, as the card suggests
7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented

## Questions

### Which is better for AI agents, MiniMax-M2.5 or Qwen3-4B-Instruct-2507?

MiniMax-M2.5 scores 57.5 (C) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 1 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach and risk.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minimax-m2-5", "b": "qwen3-4b-instruct-2507"}`. From a terminal: `anchor compare minimax-m2-5 qwen3-4b-instruct-2507`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json and https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.json

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- [MiniMax-M2.5 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-27b.md)
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- [MiniMax-M2.5 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-2b-instruct.md)
- [MiniMax-M2.5 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-30b-a3b-instruct.md)
- [MiniMax-M2.5 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-32b-instruct.md)
- [MiniMax-M2.5 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-4b-instruct.md)
- [MiniMax-M2.5 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-8b-instruct.md)
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- [MiniMax-M2.5 vs SmolLM3-3B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-smollm3-3b.md)
- [MiniMax-M2.5 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-spark-x2-6-4b.md)
- [MiniMax-M2.5 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-27b.md)
- [MiniMax-M2.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next.md)
- [MiniMax-M2.5 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/minimax-m2-5-vs-thinkingcap-qwen3-8-27b.md)
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- [Muse Glimmer 30B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-4b-instruct-2507.md)
- [Nemotron 3.5 Lightning 30B A3B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-4b-instruct-2507.md)
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- [occamy-1.0 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.md)
- [Olmo 3 7B Think vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507.md)
- [Ornith-1.5-35B-A3B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-4b-instruct-2507.md)
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- [Ornith-1.5-9B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-4b-instruct-2507.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-4b-instruct-2507.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-122b-a10b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-2b.md)
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- [Qwen3-4B-Instruct-2507 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-omni-30b-a3b-instruct.md)
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- [Qwen3-4B-Instruct-2507 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3-4B-Instruct-2507 vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b.md)
- [Qwen3-4B-Instruct-2507 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b.md)
- [Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next.md)
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