# Kimi K3.1 Pro vs Qwen3-30B-A3B-Instruct-2507 (slim)

> Qwen3-30B-A3B-Instruct-2507 scores 56.6 (C) to Kimi K3.1 Pro's 48.6 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen3-30b-a3b-instruct-2507.md (~10,150 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen3-30b-a3b-instruct-2507.json · canonical https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen3-30b-a3b-instruct-2507
- 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)

Qwen3-30B-A3B-Instruct-2507 scores 56.6 (C) on agent readiness against Kimi K3.1 Pro's 48.6 (D), and leads in 3 of 4 scored categories. Kimi K3.1 Pro leads on documentation and upkeep. Both do open-weight models you run yourself.

- Kimi K3.1 Pro: D 48.6, rank #151 of 160 open-weight models · https://www.anchorterminal.com/tools/kimi-k3-1-pro.min.md
- Qwen3-30B-A3B-Instruct-2507: C 56.6, rank #113 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-30b-a3b-instruct-2507.min.md
- Kimi K3.1 Pro, good for Operators with a multi-accelerator node who want Moonshot's newest open-weight model for coding and long agent sessions, and everyone else through an API Ahead on Documentation and upkeep, 51 against 26.
- Qwen3-30B-A3B-Instruct-2507, good for Agents that want an instruct model with tool calling on one 24 GB GPU or a 32 GB Mac, with a plain licence and a 262,144-token context. Ahead on Reach, 90 against 40; Risk, 55 against 50; Agent interface, 75 against 65.

| Category | Kimi K3.1 Pro | Qwen3-30B-A3B-Instruct-2507 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 90 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 65 | 75 |
| Documentation and upkeep (10%) | 51 | 26 |

| Fact (where they differ) | Kimi K3.1 Pro | Qwen3-30B-A3B-Instruct-2507 |
| --- | --- | --- |
| Vendor | Moonshot AI | Alibaba (Qwen team) |
| Licence | Kimi K3.1 Pro License (modified MIT) | Apache-2.0 |
| Last release | 2026-11-05 | 2025-09-17 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Qwen3-30B-A3B-Instruct-2507 +50: Kimi K3.1 Pro 40 (Memory 0, the only build is Moonshot's 1,561 GB MXFP4 release, far above 256 GB.); Qwen3-30B-A3B-Instruct-2507 90 (Memory 25 of 30, LM Studio's MLX 4-bit build is 17.2 GB and Ollama's 4-bit build 19 GB, 21 to 23 GB with a fifth added, which fits 24 GB.)
- Documentation and upkeep, Kimi K3.1 Pro +25: Kimi K3.1 Pro 51 (Model card 11, no limitations, languages or cut-off.); Qwen3-30B-A3B-Instruct-2507 26 (Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, named languages and a knowledge cut-off aren't.)
- Agent interface, Qwen3-30B-A3B-Instruct-2507 +10: Kimi K3.1 Pro 65 (Chat template 10, the format is only code to run.); Qwen3-30B-A3B-Instruct-2507 75 (Chat template 20, a Jinja template in tokenizer_config.json.)
- Risk, Qwen3-30B-A3B-Instruct-2507 +5: Kimi K3.1 Pro 50 (File safety 15, safetensors only, less 10 for remote code and prompts built by the repository's script.); Qwen3-30B-A3B-Instruct-2507 55 (File safety 25, safetensors only and nothing from the repository runs to load it or build prompts.)