# Gemma 4 E2B IT vs MiniCPM5-2B

> Gemma 4 E2B IT and MiniCPM5-2B score within a point of each other for open-weight models you run yourself, 60.4 and 60.2 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b
- Markdown: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.md (~6,050 tokens)
- Slim: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: 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)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Gemma 4 E2B IT and MiniCPM5-2B score within a point of each other on agent readiness, 60.4 (C) and 60.2 (C). MiniCPM5-2B leads on capability and documentation and upkeep. Both do open-weight models you run yourself.

- Gemma 4 E2B IT: grade C, 60.4/100, rank #54 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gemma-4-e2b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/gemma-4-e2b-it.json
- MiniCPM5-2B: grade C, 60.2/100, rank #56 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Gemma 4 E2B IT (C)

Good 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 90
- Risk, 70 against 55
- Agent interface, 85 against 75

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

### MiniCPM5-2B (C)

Good for: On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data

Ahead on:
- Capability, 27 against 19
- Documentation and upkeep, 97 against 75

Watch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning


## Score by category

| Category | Weight | Gemma 4 E2B IT | MiniCPM5-2B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 19 | 27 | MiniCPM5-2B +8 |
| Reach | 25% (25 this run) | 95 | 90 | Gemma 4 E2B IT +5 |
| Risk | 20% (20 this run) | 70 | 55 | Gemma 4 E2B IT +15 |
| Agent interface | 10% (10 this run) | 85 | 75 | Gemma 4 E2B IT +10 |
| Documentation and upkeep | 10% (10 this run) | 75 | 97 | MiniCPM5-2B +22 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **60.4 · C** | **60.2 · C** | |

## Facts side by side

| Fact | Gemma 4 E2B IT | MiniCPM5-2B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | OpenBMB |
| 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 | 2026-09-29 |
| 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.

**MiniCPM5-2B.** A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.

## Before you call either

### Gemma 4 E2B IT

1. 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 `--mmproj` with gemma-4-E2B-it-mmproj.gguf for images and audio
2. With Ollama run `ollama run gemma4:e2b` 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

### MiniCPM5-2B

1. Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m)
2. On vLLM 0.29.0 or later run `vllm serve openbmb/MiniCPM5-2B --max-model-len 131072 --enable-auto-tool-choice --tool-call-parser minicpm5`, or tool calls come back as XML text
3. On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls
4. Tool calls are XML, `<function name=...><param name=...>`, not Hermes JSON
5. Sample with temperature 1.0, top_p 0.95 and min_p 0.0; llama.cpp's default min_p 0.05 can loop, and repetition_penalty 1.05 helps if it does
6. Expect a `<think>` block before every answer and leave room in max_tokens; enable_thinking false is accepted by the template but OpenBMB doesn't support it for the 2B
7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented
8. Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix

## Questions

### Which is better for AI agents, Gemma 4 E2B IT or MiniCPM5-2B?

Gemma 4 E2B IT and MiniCPM5-2B score within a point of each other on agent readiness, 60.4 (C) and 60.2 (C). MiniCPM5-2B leads on capability and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemma-4-e2b-it", "b": "minicpm5-2b"}`. From a terminal: `anchor compare gemma-4-e2b-it minicpm5-2b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemma-4-e2b-it.json and https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json

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