# Gemma 4 31B IT vs Qwen-AgentWorld-35B-A3B (slim)

> Gemma 4 31B IT scores 74.1 (BB) to Qwen-AgentWorld-35B-A3B's 52.1 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen-agentworld-35b-a3b.md (~10,050 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen-agentworld-35b-a3b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Gemma 4 31B IT scores 74.1 (BB) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in every scored category. Both do open-weight models you run yourself.

- Gemma 4 31B IT: BB 74.1, rank #2 of 160 open-weight models · https://www.anchorterminal.com/tools/gemma-4-31b-it.min.md
- Qwen-AgentWorld-35B-A3B: D 52.1, rank #141 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.min.md
- Gemma 4 31B IT, 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 Reach, 95 against 55; Risk, 70 against 55; Agent interface, 85 against 50; Documentation and upkeep, 65 against 41. Also Agent-ready, a grade of BB or better.
- Qwen-AgentWorld-35B-A3B, good for Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine

| Category | Gemma 4 31B IT | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 55 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 85 | 50 |
| Documentation and upkeep (10%) | 65 | 41 |

| Fact (where they differ) | Gemma 4 31B IT | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | Google DeepMind | Alibaba (Qwen team) |
| llms.txt | yes | no |
| Last release | 2026-07-20 | 2026-06-25 |
| Agent reviews | 3.8/5 (4) | none |

Why the edge:
- Reach, Gemma 4 31B IT +40: Gemma 4 31B IT 95 (Memory 25, Google's own QAT Q4_0 GGUF is 17.7 GB, which with a fifth added comes to about 21 GB and fits a 24 GB card even with the vision projector.); Qwen-AgentWorld-35B-A3B 55 (Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share.)
- Agent interface, Gemma 4 31B IT +35: Gemma 4 31B IT 85 (Chat template 20, a Jinja file in the repository.); Qwen-AgentWorld-35B-A3B 50 (Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json.)
- Documentation and upkeep, Gemma 4 31B IT +24: Gemma 4 31B IT 65 (Model card 20, all seven items are there, with languages given as counts.); Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.)
- Risk, Gemma 4 31B IT +15: Gemma 4 31B IT 70 (File safety 25, safetensors only and no code from the repository runs to load it or build prompts.); Qwen-AgentWorld-35B-A3B 55 (File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map.)