# Inkling vs Qwen3.5-122B-A10B (slim)

> Inkling and Qwen3.5-122B-A10B score within a point of each other for open-weight models you run yourself, 64.2 and 63.6 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b.md (~6,050 tokens) · this version ~430 tokens · JSON https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b.json · canonical https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-21
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Inkling and Qwen3.5-122B-A10B score within a point of each other on agent readiness, 64.2 (B) and 63.6 (B). Qwen3.5-122B-A10B leads on reach. Both do open-weight models you run yourself.

- Inkling: B 64.2, rank #20 of 100 open-weight models · https://www.anchorterminal.com/tools/inkling.min.md
- Qwen3.5-122B-A10B: B 63.6, rank #22 of 100 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-122b-a10b.min.md
- Inkling, good for Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves. Ahead on Risk, 70 against 55; Agent interface, 85 against 70; Documentation and upkeep, 82 against 39.
- Qwen3.5-122B-A10B, good for Agents with a 128 GB unified-memory machine or two large GPUs that want a capable vision-language model with a plain licence. Ahead on Reach, 80 against 50.

| Category | Inkling | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Capability (35%) | 60 | 62 |
| Reach (25%) | 50 | 80 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 82 | 39 |

| Fact (where they differ) | Inkling | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Vendor | Thinking Machines Lab | Alibaba (Qwen team) |
| Last release | 2026-07-23 | 2026-02-24 |
