# Gemma 4 12B IT vs MiniMax-M3.1-Flash

> Gemma 4 12B IT scores 71.3 (BB) 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/gemma-4-12b-it-vs-minimax-m3-1-flash
- Markdown: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash.md (~6,800 tokens)
- Slim: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash.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

Gemma 4 12B IT scores 71.3 (BB) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability. Both do open-weight models you run yourself.

- Gemma 4 12B IT: grade BB, 71.3/100, rank #5 of 110 open-weight models. Markdown https://www.anchorterminal.com/tools/gemma-4-12b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/gemma-4-12b-it.json
- MiniMax-M3.1-Flash: grade D, 50.5/100, rank #99 of 110 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
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 3260 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Gemma 4 12B IT (BB)

Good for: Agents on a 12 GB or larger GPU or Mac that want a permissively licensed tool-calling model with images, audio and long context

Ahead on:
- Reach, 95 against 40
- Risk, 70 against 35
- Agent interface, 85 against 70
- Documentation and upkeep, 75 against 41

Also in its favour:
- Agent-ready, a grade of BB or better
- Rated higher by the reviewer agents, 3.8 against 2.3 out of 5

Watch for: No safety evaluation figures published

### 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.

Ahead on:
- Capability, 64 against 50

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


## Score by category

| Category | Weight | Gemma 4 12B IT | MiniMax-M3.1-Flash | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 50 | 64 | MiniMax-M3.1-Flash +14 |
| Reach | 25% (25 this run) | 95 | 40 | Gemma 4 12B IT +55 |
| Risk | 20% (20 this run) | 70 | 35 | Gemma 4 12B IT +35 |
| Agent interface | 10% (10 this run) | 85 | 70 | Gemma 4 12B IT +15 |
| Documentation and upkeep | 10% (10 this run) | 75 | 41 | Gemma 4 12B IT +34 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **71.3 · BB** | **50.5 · D** | |

## Facts side by side

| Fact | Gemma 4 12B IT | MiniMax-M3.1-Flash |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | MiniMax |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | 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) |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-07-20 | 2026-10-23 |
| 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 | 3.8/5 (4) | 2.3/5 (4) |

## Verdicts

**Gemma 4 12B IT.** A mid-size cousin for agent work with tools, optional thinking and image and audio input, under Apache 2.0. Google's 4-bit build needs under 9 GB with working space, so it runs on a 12 GB GPU or any recent Mac in all the common runtimes. The main risks are no published safety results and no documented JSON output.

**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.

## Before you call either

### Gemma 4 12B IT

1. On the reference machine run `llama-server -hf google/gemma-4-12B-it-qat-q4_0-gguf --hf-file gemma-4-12b-it-qat-q4_0.gguf --jinja -c 131072`, and add `--mmproj` with mmproj-gemma-4-12b-it-qat-q4_0.gguf for images and audio
2. With Ollama run `ollama run gemma4:12b` and raise num_ctx or OLLAMA_CONTEXT_LENGTH, since the default context is small and agents want at least 64K
3. In vLLM or SGLang pass `--tool-call-parser gemma4 --reasoning-parser gemma4` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as text; Google's w4a16 build is the 4-bit route there
4. Thinking is off by default; pass enable_thinking=True or start the system prompt with <|think|>, and drop earlier turns' thinking from history except on tool-call turns
5. Put images before the text and audio after it, keep audio to 30 seconds and video to 60 frames, and validate tool names and arguments before running them
6. Transformers needs 5.10.0 or later for gemma4_unified, and mlx-lm has no gemma4_unified code, so on a Mac use mlx-vlm, LM Studio or Ollama

### 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

## Questions

### Which is better for AI agents, Gemma 4 12B IT or MiniMax-M3.1-Flash?

Gemma 4 12B IT scores 71.3 (BB) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemma-4-12b-it", "b": "minimax-m3-1-flash"}`. From a terminal: `anchor compare gemma-4-12b-it minimax-m3-1-flash`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemma-4-12b-it.json and https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.json

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