# Qwen-AgentWorld-35B-A3B vs Spark-X2.6-4B (slim)

> Spark-X2.6-4B scores 61 (C) 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/qwen-agentworld-35b-a3b-vs-spark-x2-6-4b.md (~10,000 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-spark-x2-6-4b.json · canonical https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-spark-x2-6-4b
- 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
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Spark-X2.6-4B scores 61 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on risk. Both do open-weight models you run yourself.

- 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
- Spark-X2.6-4B: C 61, rank #56 of 160 open-weight models · https://www.anchorterminal.com/tools/spark-x2-6-4b.min.md
- 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 Ahead on Risk, 55 against 50.
- Spark-X2.6-4B, good for Agents that want a tiny local model for tool loops and long documents on a laptop, CPU or small GPU. Ahead on Reach, 85 against 55; Agent interface, 70 against 50; Documentation and upkeep, 51 against 41.

| Category | Qwen-AgentWorld-35B-A3B | Spark-X2.6-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 85 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 50 | 70 |
| Documentation and upkeep (10%) | 41 | 51 |

| Fact (where they differ) | Qwen-AgentWorld-35B-A3B | Spark-X2.6-4B |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | SparkLLM (XHToken) |
| Last release | 2026-06-25 | 2026-10-20 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Spark-X2.6-4B +30: 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.); Spark-X2.6-4B 85 (Memory 30, SparkLLM's Q4_K_M GGUF is 3.19 GB, about 3.8 GB with a fifth added, which fits 8 GB.)
- Agent interface, Spark-X2.6-4B +20: Qwen-AgentWorld-35B-A3B 50 (Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json.); Spark-X2.6-4B 70 (Chat template 20, a Jinja file in the repository.)
- Documentation and upkeep, Spark-X2.6-4B +10: Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.); Spark-X2.6-4B 51 (Model card 11 of 20, intended use, parameters, context and languages, with no limitations, cut-off or architecture description of its own.)
- Risk, Qwen-AgentWorld-35B-A3B +5: Qwen-AgentWorld-35B-A3B 55 (File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map.); Spark-X2.6-4B 50 (File safety 15 of 25, safetensors and GGUF only, but the card's Transformers and vLLM routes run the repository's Python.)