# Gemma 4 12B IT vs Granite 4.2 8B

> Gemma 4 12B IT scores 72.3 (BB) to Granite 4.2 8B's 61 (C) 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-granite-4-2-8b
- Markdown: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-granite-4-2-8b.md (~8,900 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: 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)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

Gemma 4 12B IT scores 72.3 (BB) on agent readiness against Granite 4.2 8B's 61 (C), and leads in 1 of 4 scored categories. Granite 4.2 8B leads on documentation and upkeep. Both do open-weight models you run yourself.

- Gemma 4 12B IT: grade BB, 72.3/100, rank #4 of 160 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
- Granite 4.2 8B: grade C, 61/100, rank #66 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-8b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 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:
- Risk, 70 against 55

Also in its favour:
- Agent-ready, a grade of BB or better

Watch for: No safety evaluation figures published

### Granite 4.2 8B (C)

Good for: Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 16 GB machine

Ahead on:
- Documentation and upkeep, 92 against 85

Watch for: No safety results published for it


## Why the edge

### Risk: Gemma 4 12B IT +15

- Gemma 4 12B IT (70): File safety 25, safetensors and GGUF only, with nothing from the repository run on load. Provenance 15, the files sit in Google's own organisation and every file has a checksum. Safety evaluation 0, the card says testing showed minimal policy violations but gives no figures. Agent guidance 10, the card names the harm categories its safety training covers and asks for content-safety safeguards, and the tool guide says to validate calls, with no prompt-injection guidance. Licence risk 15, Apache 2.0 with no added policy, no threshold and a working link. Security programme 5, Google's security.txt and reward programme give a route to report a flaw, but no public Gemma advisories were found.
- Granite 4.2 8B (55): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ibm-granite organisation, which IBM's Granite docs and the GitHub README link to (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, and the card's licence link resolves. Security programme 5, www.ibm.com/.well-known/security.txt names IBM PSIRT, read for the 3B listing on 4 November 2026 (5). 15 + 15 + 0 + 5 + 15 + 5 = 55.

### Documentation and upkeep: Granite 4.2 8B +7

- Gemma 4 12B IT (85): Model card 20, all seven items are there. Training data 10, a general description by type with a January 2025 cut-off and the filtering, but no sources, mix or sizes. Last change 20, Google merged a fix for 210 glitch tokens in tokenizer.json on 30 October 2026, two days before 1 November. Responsiveness 20, Google replied to 18 of 34 questions and reports, the last on 2026-07-31, re-counted on 1 November. Version policy 10, earlier Gemma generations keep their own repositories and gemma.ai has a dated releases page. File health 5, the files agree with the card but a report about them waits without a reply.
- Granite 4.2 8B (92): Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (8B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 8B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 20, the last commit, on 20 October 2026, replaced model.safetensors.index.json (titled "granite-4.2 index file fix"), 21 days before this check. Responsiveness 20, Of the 5 discussions that aren't pull requests (13 September to 5 November 2026), 4 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 8B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 20 + 20 + 5 + 10 = 92.

## Score by category

| Category | Weight | Gemma 4 12B IT | Granite 4.2 8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 95 | 95 | even |
| Risk | 20% (20 this run) | 70 | 55 | Gemma 4 12B IT +15 |
| Agent interface | 10% (10 this run) | 85 | 85 | even |
| Documentation and upkeep | 10% (10 this run) | 85 | 92 | Granite 4.2 8B +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **72.3 · BB** | **61 · C** | |

## Facts side by side

| Fact | Gemma 4 12B IT | Granite 4.2 8B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | IBM |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-07-20 | 2026-10-20 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 3.8/5 (4) | none |

## How the scores have moved

### Gemma 4 12B IT

- +1.0 on 1 November 2026: product

### Granite 4.2 8B

No score change since it was listed.

## 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.

**Granite 4.2 8B.** IBM's mid-size reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 16 GB machine, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.

## 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

### Granite 4.2 8B

1. Start it with `ollama run granite4.2:8b`, or `llama-server -hf ibm-granite/granite-4.2-8b-GGUF:Q4_K_M --jinja`
2. With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`
3. Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning
4. The context is 131,072 tokens. The card's 512K extension isn't documented
5. Validate JSON output yourself, since structured output isn't documented
6. IBM recommends Granite Guardian beside it to flag risky inputs and outputs

## Questions

### Which is better for AI agents, Gemma 4 12B IT or Granite 4.2 8B?

Gemma 4 12B IT scores 72.3 (BB) on agent readiness against Granite 4.2 8B's 61 (C), and leads in 1 of 4 scored categories. Granite 4.2 8B leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-granite-4-2-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-granite-4-2-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemma-4-12b-it", "b": "granite-4-2-8b"}`. From a terminal: `anchor compare gemma-4-12b-it granite-4-2-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemma-4-12b-it.json and https://www.anchorterminal.com/api/v1/tools/granite-4-2-8b.json

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- [Gemma 4 12B IT vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-30b-a3b-instruct-2507.md)
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- [Gemma 4 12B IT vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-0-8b.md)
- [Gemma 4 12B IT vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-122b-a10b.md)
- [Gemma 4 12B IT vs Qwen3.5-2B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-2b.md)
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- [Gemma 4 12B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-4b.md)
- [Gemma 4 12B IT vs Qwen3.5-9B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-9b.md)
- [Gemma 4 12B IT vs Qwen3.6-27B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-6-27b.md)
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- [Gemma 4 12B IT vs Qwen3.8-27B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-8-27b.md)
- [Gemma 4 12B IT vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-8-flash-next.md)
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- [Gemma 4 12B IT vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-vl-30b-a3b-instruct.md)
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- [Granite 4.2 8B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-30b-a3b-instruct-2507.md)
- [Granite 4.2 8B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-4b-instruct-2507.md)
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- [Granite 4.2 8B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-4b.md)
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- [Granite 4.2 8B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-coder-next.md)
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- [Granite 4.2 8B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-2b.md)
- [Granite 4.2 8B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-4b.md)
- [Granite 4.2 8B vs ZAYA1-8B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-zaya1-8b.md)

---

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