Head to head · Open-weight models you run yourself · October 2026 research run
Gemma 4 26B A4B IT vs occamy-1.0
Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against occamy-1.0's 61 (C), and leads in 3 of 4 scored categories. occamy-1.0 leads on documentation and upkeep. 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 26B A4B ITGoogle DeepMind · Open-weight model
BB72.2/100#4 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 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context
Ahead on
- Reach, 90 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.
Ahead on
- Documentation and upkeep, 74 against 65
Watch for
No safety results, prompt-injection guidance or security contact
Score by category
| Category | Weight this run | Gemma 4 26B A4B IT | occamy-1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 90 | 85 | Gemma 4 26B A4B IT +5 |
| Risk | 20%20 | 70 | 55 | Gemma 4 26B A4B IT +15 |
| Agent interface | 10%10 | 85 | 70 | Gemma 4 26B A4B IT +15 |
| Documentation and upkeep | 10%10 | 65 | 74 | occamy-1.0 +9 |
| Negative events | ≤15 | 0 | 0 | |
| Total | BB 72.2/100 | C 61/100 |
Facts side by side
| Fact | Gemma 4 26B A4B 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 | no | 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 26B A4B IT
A fast mixture-of-experts cousin for general agent work with tools, optional thinking and image input, under Apache 2.0. Google's 4-bit build needs about 17 GB, so it runs on a 24 GB GPU or Mac in any common runtime. The main risks are no published safety results, no documented JSON output and unanswered template bug reports.
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 26B A4B IT
- On the reference machine run
llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf --hf-file gemma-4-26B_q4_0-it.gguf --jinja -c 65536, and add the mmproj file for images - With Ollama run
ollama run gemma4:26band raise num_ctx or OLLAMA_CONTEXT_LENGTH, since Google's guide says it defaults to 4K below 24 GiB of VRAM 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 - 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
- Validate tool names and arguments before running them, and check any JSON yourself
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 26B A4B IT or occamy-1.0?
Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against occamy-1.0's 61 (C), and leads in 3 of 4 scored categories. occamy-1.0 leads on documentation and upkeep.
Other comparisons with Gemma 4 26B A4B IT or occamy-1.0
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- Agents-A1-4B vs occamy-1.0
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- Apodex-1.1-mini vs Gemma 4 26B A4B IT
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- Darwin-36B-Opus vs Gemma 4 26B A4B IT
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- Gemma 4 12B IT vs Gemma 4 26B A4B IT
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- Gemma 4 26B A4B IT vs Gemma 4 31B IT
- Gemma 4 26B A4B IT vs Gemma 4 E2B IT
- Gemma 4 26B A4B IT vs Gemma 4 E4B IT
- Gemma 4 26B A4B IT vs GLM-4.5-Air
- Gemma 4 26B A4B IT vs GLM-4.7-Flash
- Gemma 4 26B A4B IT vs GLM-5.3
- Gemma 4 26B A4B IT vs GLM-5.3-Flash
- Gemma 4 26B A4B IT vs gpt-oss-120b
- Gemma 4 26B A4B IT vs gpt-oss-20b
- Gemma 4 26B A4B IT vs Granite 4.2 3B
- Gemma 4 26B A4B IT vs Hy3
- Gemma 4 26B A4B IT vs Inkling
- Gemma 4 26B A4B IT vs Inkling-Small
- Gemma 4 26B A4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview
- Gemma 4 26B A4B IT vs Kimi K3
- Gemma 4 26B A4B IT vs Kolibri-1
- Gemma 4 26B A4B IT vs Laguna M.1
- Gemma 4 26B A4B IT vs Laguna S 2.1
- Gemma 4 26B A4B IT vs Laguna XS 2.1
- Gemma 4 26B A4B IT vs LFM2.5-2.6B
- Gemma 4 26B A4B IT vs Ling-3.0-tiny
- Gemma 4 26B A4B IT vs MiMo-V2.6 Distill Qwen 9B
- Gemma 4 26B A4B IT vs MiniCPM-o 4.5
- Gemma 4 26B A4B IT vs MiniCPM5-2B
- Gemma 4 26B A4B IT vs MiniMax-M2.5
- Gemma 4 26B A4B IT vs MiniMax-M2.7
- Gemma 4 26B A4B IT vs Muse Glimmer 30B
- Gemma 4 26B A4B IT vs Nemotron 3.5 Lightning 30B A3B
- Gemma 4 26B A4B IT vs Nemotron 3 Nano 30B A3B
- Gemma 4 26B A4B IT vs Nemotron 3 Nano 4B
- Gemma 4 26B A4B IT vs Nemotron 3 Nano Omni 30B A3B Reasoning
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- Gemma 4 26B A4B IT vs Qwen3-Coder-Next
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- Gemma 4 26B A4B IT vs Qwen3-VL-2B-Instruct
- Gemma 4 26B A4B IT vs Qwen3-VL-30B-A3B-Instruct
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- Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-27B
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- Gemma 4 E4B IT vs occamy-1.0
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- GLM-4.7-Flash vs occamy-1.0
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- 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
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- 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
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- occamy-1.0 vs Ornith-1.5-9B
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- 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
- 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-4-26b-a4b-it-vs-occamy-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/gemma-4-26b-a4b-it.json·/api/v1/tools/occamy-1-0.json - From a terminal
anchor compare gemma-4-26b-a4b-it occamy-1-0(the CLI) - Over MCP
compare_tools {"a": "gemma-4-26b-a4b-it", "b": "occamy-1-0"}at/mcp, no key