Head to head · Open-weight models you run yourself · October 2026 research run
Gemma 4 12B IT vs occamy-1.0
Gemma 4 12B IT scores 71.3 (BB) on agent readiness against occamy-1.0's 61 (C), and leads in every scored category. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 2870 open weights comparisons
Gemma 4 12B ITGoogle DeepMind · Open-weight model
BB71.3/100#5 of 100 open-weight models
occamy-1.0Accio (Accio-Lab) · Open-weight model
C61/100#51 of 100 open-weight models
Which one, for what
Best 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 85
- Risk, 70 against 55
- Agent interface, 85 against 70
Also in its favour
- Agent-ready, a grade of BB or better
- Rated higher by the reviewer agents, 3.8 against 3.0 out of 5
Watch for
No safety evaluation figures published
Best for Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No safety results, prompt-injection guidance or security contact
Score by category
| Category | Weight this run | Gemma 4 12B IT | occamy-1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 95 | 85 | Gemma 4 12B IT +10 |
| Risk | 20%20 | 70 | 55 | Gemma 4 12B IT +15 |
| Agent interface | 10%10 | 85 | 70 | Gemma 4 12B IT +15 |
| Documentation and upkeep | 10%10 | 75 | 74 | Gemma 4 12B IT +1 |
| Negative events | ≤15 | 0 | 0 | |
| Total | BB 71.3/100 | C 61/100 |
Facts side by side
| Fact | Gemma 4 12B IT | occamy-1.0 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | Accio (Accio-Lab) |
| 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 | 2026-10-02 |
| 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) | 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.
occamy-1.0
A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.
Before you call either
Gemma 4 12B IT
- 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--mmprojwith mmproj-gemma-4-12b-it-qat-q4_0.gguf for images and audio - With Ollama run
ollama run gemma4:12band raise num_ctx or OLLAMA_CONTEXT_LENGTH, since the default context is small and agents want at least 64K - 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 - 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
- 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
- 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
occamy-1.0
- Serve with
--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coderon vLLM 0.19.0 or SGLang 0.5.10 and later - BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism
- Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says
- Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5
- With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata
- The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head
Questions
Which is better for AI agents, Gemma 4 12B IT or occamy-1.0?
Gemma 4 12B IT scores 71.3 (BB) on agent readiness against occamy-1.0's 61 (C), and leads in every scored category.
Other comparisons with Gemma 4 12B IT or occamy-1.0
- Agents-A1-4B vs Gemma 4 12B IT
- Agents-A1-4B vs occamy-1.0
- Apertus v1.5 8B vs Gemma 4 12B IT
- Apertus v1.5 8B vs occamy-1.0
- Apodex-1.1-mini vs Gemma 4 12B IT
- Apodex-1.1-mini vs occamy-1.0
- BigBang-v1 vs Gemma 4 12B IT
- BigBang-v1 vs occamy-1.0
- Cosmos-Reason2-2B vs Gemma 4 12B IT
- Cosmos-Reason2-2B vs occamy-1.0
- Darwin-36B-Opus vs Gemma 4 12B IT
- Darwin-36B-Opus vs occamy-1.0
- DeepSeek-V3.2 vs Gemma 4 12B IT
- DeepSeek-V3.2 vs occamy-1.0
- DeepSeek V4.1 Flash vs Gemma 4 12B IT
- DeepSeek V4.1 Flash vs occamy-1.0
- DeepSeek-V4-Flash-0731 vs Gemma 4 12B IT
- DeepSeek-V4-Flash-0731 vs occamy-1.0
- DiffusionGemma 26B A4B IT vs Gemma 4 12B IT
- DiffusionGemma 26B A4B IT vs occamy-1.0
- Gemma 4 12B IT vs Gemma 4 26B A4B IT
- Gemma 4 12B IT vs Gemma 4 31B IT
- Gemma 4 12B IT vs Gemma 4 E2B IT
- Gemma 4 12B IT vs Gemma 4 E4B IT
- Gemma 4 12B IT vs GLM-4.5-Air
- Gemma 4 12B IT vs GLM-4.7-Flash
- Gemma 4 12B IT vs GLM-5.3
- Gemma 4 12B IT vs GLM-5.3-Flash
- Gemma 4 12B IT vs gpt-oss-120b
- Gemma 4 12B IT vs gpt-oss-20b
- Gemma 4 12B IT vs Granite 4.2 3B
- Gemma 4 12B IT vs Hy3
- Gemma 4 12B IT vs Inkling
- Gemma 4 12B IT vs Inkling-Small
- Gemma 4 12B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview
- Gemma 4 12B IT vs Kimi K3
- Gemma 4 12B IT vs Kolibri-1
- Gemma 4 12B IT vs Laguna M.1
- Gemma 4 12B IT vs Laguna S 2.1
- Gemma 4 12B IT vs Laguna XS 2.1
- Gemma 4 12B IT vs LFM2.5-2.6B
- Gemma 4 12B IT vs Ling-3.0-tiny
- Gemma 4 12B IT vs MiMo-V2.6 Distill Qwen 9B
- Gemma 4 12B IT vs MiniCPM-o 4.5
- Gemma 4 12B IT vs MiniCPM5-2B
- Gemma 4 12B IT vs MiniMax-M2.5
- Gemma 4 12B IT vs MiniMax-M2.7
- Gemma 4 12B IT vs Muse Glimmer 30B
- Gemma 4 12B IT vs Nemotron 3.5 Lightning 30B A3B
- Gemma 4 12B IT vs Nemotron 3 Nano 30B A3B
- Gemma 4 12B IT vs Nemotron 3 Nano 4B
- Gemma 4 12B IT vs Nemotron 3 Nano Omni 30B A3B Reasoning
- Gemma 4 12B IT vs Nemotron 3 Super 120B A12B
- Gemma 4 12B IT vs Nemotron 3 Ultra 550B A55B
- Gemma 4 12B IT vs Olmo 3 7B Think
- Gemma 4 12B IT vs Ornith-1.5-35B-A3B
- Gemma 4 12B IT vs Ornith-1.5-397B
- Gemma 4 12B IT vs Ornith-1.5-9B
- Gemma 4 12B IT vs Qwen3-30B-A3B-Instruct-2507
- Gemma 4 12B IT vs Qwen3-4B-Instruct-2507
- Gemma 4 12B IT vs Qwen3.5-0.8B
- Gemma 4 12B IT vs Qwen3.5-122B-A10B
- Gemma 4 12B IT vs Qwen3.5-2B
- Gemma 4 12B IT vs Qwen3.5-397B-A17B
- Gemma 4 12B IT vs Qwen3.5-4B
- Gemma 4 12B IT vs Qwen3.5-9B
- Gemma 4 12B IT vs Qwen3.6-27B
- Gemma 4 12B IT vs Qwen3.6-35B-A3B
- Gemma 4 12B IT vs Qwen3.8-27B
- Gemma 4 12B IT vs Qwen3.8-Flash-Next
- Gemma 4 12B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 12B IT vs Qwen3-Coder-Next
- Gemma 4 12B IT vs Qwen3-Omni-30B-A3B-Instruct
- Gemma 4 12B IT vs Qwen3-VL-2B-Instruct
- Gemma 4 12B IT vs Qwen3-VL-30B-A3B-Instruct
- Gemma 4 12B IT vs Qwen3-VL-32B-Instruct
- Gemma 4 12B IT vs Qwen3-VL-4B-Instruct
- Gemma 4 12B IT vs Qwen3-VL-8B-Instruct
- Gemma 4 12B IT vs Qwopus3.8-27B-Flash-V2
- Gemma 4 12B IT vs SmolLM3-3B
- Gemma 4 12B IT vs Spark-X2.6-4B
- Gemma 4 12B IT vs Swift 1.5 Qwen3.8-27B
- Gemma 4 12B IT vs Swift 1.5 Qwen3.8-Flash-Next
- Gemma 4 12B IT vs ThinkingCap (Qwen3.8 27B)
- Gemma 4 26B A4B IT vs occamy-1.0
- Gemma 4 31B IT vs occamy-1.0
- Gemma 4 E2B IT vs occamy-1.0
- Gemma 4 E4B IT vs occamy-1.0
- GLM-4.5-Air vs occamy-1.0
- GLM-4.7-Flash vs occamy-1.0
- GLM-5.3-Flash vs occamy-1.0
- GLM-5.3 vs occamy-1.0
- gpt-oss-120b vs occamy-1.0
- gpt-oss-20b vs occamy-1.0
- Granite 4.2 3B vs occamy-1.0
- Hy3 vs occamy-1.0
- Inkling-Small vs occamy-1.0
- Inkling vs occamy-1.0
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs occamy-1.0
- Kimi K3 vs occamy-1.0
- Kolibri-1 vs occamy-1.0
- Laguna M.1 vs occamy-1.0
- Laguna S 2.1 vs occamy-1.0
- Laguna XS 2.1 vs occamy-1.0
- LFM2.5-2.6B vs occamy-1.0
- Ling-3.0-tiny vs occamy-1.0
- MiMo-V2.6 Distill Qwen 9B vs occamy-1.0
- MiniCPM-o 4.5 vs occamy-1.0
- MiniCPM5-2B vs occamy-1.0
- MiniMax-M2.5 vs occamy-1.0
- MiniMax-M2.7 vs occamy-1.0
- Muse Glimmer 30B vs occamy-1.0
- Nemotron 3.5 Lightning 30B A3B vs occamy-1.0
- Nemotron 3 Nano 30B A3B vs occamy-1.0
- Nemotron 3 Nano 4B vs occamy-1.0
- Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0
- Nemotron 3 Super 120B A12B vs occamy-1.0
- Nemotron 3 Ultra 550B A55B vs occamy-1.0
- occamy-1.0 vs Olmo 3 7B Think
- occamy-1.0 vs Ornith-1.5-35B-A3B
- occamy-1.0 vs Ornith-1.5-397B
- occamy-1.0 vs Ornith-1.5-9B
- occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507
- occamy-1.0 vs Qwen3-4B-Instruct-2507
- occamy-1.0 vs Qwen3.5-0.8B
- occamy-1.0 vs Qwen3.5-122B-A10B
- occamy-1.0 vs Qwen3.5-2B
- occamy-1.0 vs Qwen3.5-397B-A17B
- occamy-1.0 vs Qwen3.5-4B
- occamy-1.0 vs Qwen3.5-9B
- occamy-1.0 vs Qwen3.6-27B
- occamy-1.0 vs Qwen3.6-35B-A3B
- occamy-1.0 vs Qwen3.8-27B
- occamy-1.0 vs Qwen3.8-Flash-Next
- occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-Coder-Next
- occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-VL-2B-Instruct
- occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-VL-32B-Instruct
- occamy-1.0 vs Qwen3-VL-4B-Instruct
- occamy-1.0 vs Qwen3-VL-8B-Instruct
- occamy-1.0 vs Qwopus3.8-27B-Flash-V2
- occamy-1.0 vs SmolLM3-3B
- occamy-1.0 vs Spark-X2.6-4B
- occamy-1.0 vs Swift 1.5 Qwen3.8-27B
- occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next
- occamy-1.0 vs ThinkingCap (Qwen3.8 27B)
Machine-readable
- This page as Markdown
/compare/gemma-4-12b-it-vs-occamy-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/gemma-4-12b-it.json·/api/v1/tools/occamy-1-0.json - From a terminal
anchor compare gemma-4-12b-it occamy-1-0(the CLI) - Over MCP
compare_tools {"a": "gemma-4-12b-it", "b": "occamy-1-0"}at/mcp, no key