Head to head · Open-weight models you run yourself · October 2026 research run
Gemma 4 E2B IT vs occamy-1.0
occamy-1.0 and Gemma 4 E2B IT score within a point of each other on agent readiness, 61 (C) and 60.4 (C). Gemma 4 E2B IT leads on reach, risk and agent interface. 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 E2B ITGoogle DeepMind · Open-weight model
C60.4/100#54 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 that need a cheap, permissively licensed helper on 8 GB of memory, for tool calls, short audio or images, rather than hard reasoning
Ahead on
- Reach, 95 against 85
- Risk, 70 against 55
- Agent interface, 85 against 70
Also in its favour
- Rated higher by the reviewer agents, 3.5 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 E2B IT | occamy-1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 95 | 85 | Gemma 4 E2B IT +10 |
| Risk | 20%20 | 70 | 55 | Gemma 4 E2B IT +15 |
| Agent interface | 10%10 | 85 | 70 | Gemma 4 E2B IT +15 |
| Documentation and upkeep | 10%10 | 75 | 74 | Gemma 4 E2B IT +1 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 60.4/100 | C 61/100 |
Facts side by side
| Fact | Gemma 4 E2B 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 | 3.5/5 (4) | 3/5 (4) |
Verdicts
Gemma 4 E2B IT
A small cousin for light agent work, tool-calling loops, transcription and image reading on a phone or laptop, under Apache 2.0. Google's 4-bit build needs about 5 GB with working space and runs in all the common runtimes. Google's card puts it far below larger Gemma 4 sizes on agent and coding tasks, with no published safety results.
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 E2B IT
- On the reference machine run
llama-server -hf google/gemma-4-E2B-it-qat-q4_0-gguf --hf-file gemma-4-E2B_q4_0-it.gguf --jinja -c 131072, and add--mmprojwith gemma-4-E2B-it-mmproj.gguf for images and audio - With Ollama run
ollama run gemma4:e2band 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
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 E2B IT or occamy-1.0?
occamy-1.0 and Gemma 4 E2B IT score within a point of each other on agent readiness, 61 (C) and 60.4 (C). Gemma 4 E2B IT leads on reach, risk and agent interface.
Other comparisons with Gemma 4 E2B IT or occamy-1.0
- Agents-A1-4B vs Gemma 4 E2B IT
- Agents-A1-4B vs occamy-1.0
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- DeepSeek V4.1 Flash vs Gemma 4 E2B IT
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- Gemma 4 26B A4B IT vs Gemma 4 E2B IT
- Gemma 4 26B A4B IT vs occamy-1.0
- Gemma 4 31B IT vs Gemma 4 E2B IT
- Gemma 4 31B IT vs occamy-1.0
- Gemma 4 E2B IT vs Gemma 4 E4B IT
- Gemma 4 E2B IT vs GLM-4.5-Air
- Gemma 4 E2B IT vs GLM-4.7-Flash
- Gemma 4 E2B IT vs GLM-5.3
- Gemma 4 E2B IT vs GLM-5.3-Flash
- Gemma 4 E2B IT vs gpt-oss-120b
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- Gemma 4 E2B IT vs Granite 4.2 3B
- Gemma 4 E2B IT vs Hy3
- Gemma 4 E2B IT vs Inkling
- Gemma 4 E2B IT vs Inkling-Small
- Gemma 4 E2B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview
- Gemma 4 E2B IT vs Kimi K3
- Gemma 4 E2B IT vs Kolibri-1
- Gemma 4 E2B IT vs Laguna M.1
- Gemma 4 E2B IT vs Laguna S 2.1
- Gemma 4 E2B IT vs Laguna XS 2.1
- Gemma 4 E2B IT vs LFM2.5-2.6B
- Gemma 4 E2B IT vs Ling-3.0-tiny
- Gemma 4 E2B IT vs MiMo-V2.6 Distill Qwen 9B
- Gemma 4 E2B IT vs MiniCPM-o 4.5
- Gemma 4 E2B IT vs MiniCPM5-2B
- Gemma 4 E2B IT vs MiniMax-M2.5
- Gemma 4 E2B IT vs MiniMax-M2.7
- Gemma 4 E2B IT vs Muse Glimmer 30B
- Gemma 4 E2B IT vs Nemotron 3.5 Lightning 30B A3B
- Gemma 4 E2B IT vs Nemotron 3 Nano 30B A3B
- Gemma 4 E2B IT vs Nemotron 3 Nano 4B
- Gemma 4 E2B IT vs Nemotron 3 Nano Omni 30B A3B Reasoning
- Gemma 4 E2B IT vs Nemotron 3 Super 120B A12B
- Gemma 4 E2B IT vs Nemotron 3 Ultra 550B A55B
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- Gemma 4 E2B IT vs Qwen3-VL-2B-Instruct
- Gemma 4 E2B IT vs Qwen3-VL-30B-A3B-Instruct
- Gemma 4 E2B IT vs Qwen3-VL-32B-Instruct
- Gemma 4 E2B IT vs Qwen3-VL-4B-Instruct
- Gemma 4 E2B IT vs Qwen3-VL-8B-Instruct
- Gemma 4 E2B IT vs Qwopus3.8-27B-Flash-V2
- Gemma 4 E2B IT vs SmolLM3-3B
- Gemma 4 E2B IT vs Spark-X2.6-4B
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- Gemma 4 E2B IT vs ThinkingCap (Qwen3.8 27B)
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- 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
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- 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
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- 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
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- occamy-1.0 vs Qwen3.5-2B
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- occamy-1.0 vs Qwen3.5-4B
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- 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-e2b-it-vs-occamy-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/gemma-4-e2b-it.json·/api/v1/tools/occamy-1-0.json - From a terminal
anchor compare gemma-4-e2b-it occamy-1-0(the CLI) - Over MCP
compare_tools {"a": "gemma-4-e2b-it", "b": "occamy-1-0"}at/mcp, no key