Head to head · Open-weight models you run yourself · October 2026 research run
Gemma 4 E2B IT vs Granite 4.2 8B
Granite 4.2 8B 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 risk. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons
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
- Risk, 70 against 55
Watch for
No safety evaluation figures published
Best 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 75
Watch for
No safety results published for it
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Documentation and upkeep Granite 4.2 8B +17
Gemma 4 E2B IT 75
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 233 glitch tokens in tokenizer.json on 3 November 2026, a day before 4 November. Responsiveness 10, Google replied to 9 of 24 questions and reports, the last on 2026-09-15, re-counted on 4 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.
Risk Gemma 4 E2B IT +15
Gemma 4 E2B 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.
Score by category
| Category | Weight this run | Gemma 4 E2B IT | Granite 4.2 8B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 95 | 95 | even |
| Risk | 20%20 | 70 | 55 | Gemma 4 E2B IT +15 |
| Agent interface | 10%10 | 85 | 85 | even |
| Documentation and upkeep | 10%10 | 75 | 92 | Granite 4.2 8B +17 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 60.4/100 | C 61/100 |
Facts side by side
| Fact | Gemma 4 E2B 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 | 2026-11-03 | 2026-10-20 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 3.5/5 (4) | none |
Verdicts
Gemma 4 E2B IT
A small open-weight model for light agent work, tool calls, short audio and images 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, and no safety results are published.
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 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
Granite 4.2 8B
- Start it with
ollama run granite4.2:8b, orllama-server -hf ibm-granite/granite-4.2-8b-GGUF:Q4_K_M --jinja - 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 - Thinking is on by default. Pass
enable_thinkingfalse to turn it off orlow_efforttrue for short reasoning - The context is 131,072 tokens. The card's 512K extension isn't documented
- Validate JSON output yourself, since structured output isn't documented
- IBM recommends Granite Guardian beside it to flag risky inputs and outputs
Questions
Which is better for AI agents, Gemma 4 E2B IT or Granite 4.2 8B?
Granite 4.2 8B 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 risk.
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Machine-readable
- This page as Markdown
/compare/gemma-4-e2b-it-vs-granite-4-2-8b.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/granite-4-2-8b.json - From a terminal
anchor compare gemma-4-e2b-it granite-4-2-8b(the CLI) - Over MCP
compare_tools {"a": "gemma-4-e2b-it", "b": "granite-4-2-8b"}at/mcp, no key