# Gemma 4 31B IT vs Qwen3-4B-Instruct-2507 > Gemma 4 31B IT scores 74.1 (BB) to Qwen3-4B-Instruct-2507's 55.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507 - Markdown: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507.md (~6,450 tokens) - Slim: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507.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 31B IT scores 74.1 (BB) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Both do open-weight models you run yourself. - Gemma 4 31B IT: grade BB, 74.1/100, rank #2 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gemma-4-31b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/gemma-4-31b-it.json - Qwen3-4B-Instruct-2507: grade C, 55.7/100, rank #77 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.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 31B IT (BB) Good for: An agent with a 24 GB GPU or more that wants a dense multimodal cousin with tool calling under a plain licence Ahead on: - Capability, 61 against 31 - Risk, 70 against 55 - Agent interface, 85 against 75 - Documentation and upkeep, 65 against 26 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 results published ### Qwen3-4B-Instruct-2507 (C) Good for: Agents that want a capable small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context. Watch for: No safety results, prompt-injection guidance or security contact ## Score by category | Category | Weight | Gemma 4 31B IT | Qwen3-4B-Instruct-2507 | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 61 | 31 | Gemma 4 31B IT +30 | | Reach | 25% (25 this run) | 95 | 95 | even | | Risk | 20% (20 this run) | 70 | 55 | Gemma 4 31B IT +15 | | Agent interface | 10% (10 this run) | 85 | 75 | Gemma 4 31B IT +10 | | Documentation and upkeep | 10% (10 this run) | 65 | 26 | Gemma 4 31B IT +39 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **74.1 · BB** | **55.7 · C** | | ## Facts side by side | Fact | Gemma 4 31B IT | Qwen3-4B-Instruct-2507 | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Google DeepMind | Alibaba (Qwen team) | | 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 | 2025-09-17 | | 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 31B IT.** A dense multimodal cousin with documented tool calling, optional thinking and a 256K context, for general agent work and image reading on one 24 GB GPU through Google's 4-bit build. It runs in every major runtime under plain Apache 2.0. The main risk is that Google publishes no safety results and has gone quiet on the repository since July. **Qwen3-4B-Instruct-2507.** A small, fast cousin for instruction following, short tool-calling jobs and long documents on modest hardware, with no thinking step. It runs in about 3 GB at 4 bits on every common runtime, and two providers host it. The main risk is neglect, with no file changes in over a year, no answers from Alibaba and no safety results. ## Before you call either ### Gemma 4 31B IT 1. On the reference machine run `llama-server -hf google/gemma-4-31B-it-qat-q4_0-gguf --hf-file gemma-4-31B_q4_0-it.gguf --jinja -c 32768`, adding gemma-4-31B-it-mmproj.gguf for images 2. Or `ollama run gemma4:31b` for the 20 GB Q4_K_M build 3. In vLLM serve with `--enable-auto-tool-choice --tool-call-parser gemma4 --reasoning-parser gemma4`, as vLLM's recipe does 4. Thinking is off by default, so pass `enable_thinking: true` in chat_template_kwargs to turn it on, and expect the reasoning in the thought channel block 5. Drop earlier thoughts from the history except on tool-call turns, as the card asks 6. Use the card's sampling, temperature 1.0, top_p 0.95, top_k 64 7. Validate function names and arguments before running a call, and check JSON output yourself or use the runtime's guided decoding 8. The w4a16 build relies on Marlin INT4 kernels that vLLM marks unsupported on AMD, so use the GGUF on the reference machine ### Qwen3-4B-Instruct-2507 1. Quickest start is `ollama run qwen3:4b-instruct`, 2.5 GB. Plain `qwen3:4b` is the Thinking-2507 edition, not this one 2. On our reference machine use BF16 with `vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes` 3. Use the hermes parser in vLLM or qwen25 in SGLang, the template emits JSON inside tool_call tags 4. Don't pass enable_thinking, this edition never thinks and the card says the flag isn't needed 5. Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and min_p 0, with presence_penalty up to 2 against repetition 6. Drop the context to 32,768 tokens if memory runs out, as the card suggests 7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented ## Questions ### Which is better for AI agents, Gemma 4 31B IT or Qwen3-4B-Instruct-2507? Gemma 4 31B IT scores 74.1 (BB) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-4b-instruct-2507.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemma-4-31b-it", "b": "qwen3-4b-instruct-2507"}`. 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[Hy3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/hy3-vs-qwen3-4b-instruct-2507.md) - [Inkling-Small vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.md) - [Inkling vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507.md) - [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-4b-instruct-2507.md) - [Kimi K3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507.md) - [Kolibri-1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-4b-instruct-2507.md) - [Laguna M.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.md) - [Laguna S 2.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507.md) - 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[occamy-1.0 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.md) - [Olmo 3 7B Think vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507.md) - [Ornith-1.5-35B-A3B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-4b-instruct-2507.md) - [Ornith-1.5-397B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-4b-instruct-2507.md) - [Ornith-1.5-9B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-4b-instruct-2507.md) - [Qwen3-30B-A3B-Instruct-2507 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-4b-instruct-2507.md) - [Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b.md) - [Qwen3-4B-Instruct-2507 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-122b-a10b.md) - 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[Qwen3-4B-Instruct-2507 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-30b-a3b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-omni-30b-a3b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-2b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-30b-a3b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-32b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-4b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-8b-instruct.md) - [Qwen3-4B-Instruct-2507 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwopus3-8-27b-flash-v2.md) - [Qwen3-4B-Instruct-2507 vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b.md) - [Qwen3-4B-Instruct-2507 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b.md) - [Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-27b.md) - [Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next.md) - [Qwen3-4B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b.md) --- Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp