# Inkling 2 Small vs Swift 1.5 Qwen3.8-Flash-Next (slim)

> Inkling 2 Small scores 58.8 (C) to Swift 1.5 Qwen3.8-Flash-Next's 54.2 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-12
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Inkling 2 Small scores 58.8 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 54.2 (C), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on reach. Both do open-weight models you run yourself.

- Inkling 2 Small: C 58.8, rank #102 of 161 open-weight models · https://www.anchorterminal.com/tools/inkling-2-small.min.md
- Swift 1.5 Qwen3.8-Flash-Next: C 54.2, rank #133 of 161 open-weight models · https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.min.md
- Inkling 2 Small, good for Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image. Ahead on Risk, 65 against 45; Agent interface, 85 against 60; Documentation and upkeep, 67 against 40.
- Swift 1.5 Qwen3.8-Flash-Next, good for Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work. Ahead on Reach, 65 against 40.

| Category | Inkling 2 Small | Swift 1.5 Qwen3.8-Flash-Next |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 65 |
| Risk (20%) | 65 | 45 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 67 | 40 |

| Fact (where they differ) | Inkling 2 Small | Swift 1.5 Qwen3.8-Flash-Next |
| --- | --- | --- |
| Vendor | Thinking Machines Lab | UkisAI |
| Licence | Apache-2.0 | Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue |
| Last release | 2026-11-12 | 2026-09-24 |
| Terms last updated | no document linked | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 1.8/5 (4) |

Why the edge:
- Documentation and upkeep, Inkling 2 Small +27: Inkling 2 Small 67 (Model card 17 of 20, everything but a dated knowledge cut-off.); Swift 1.5 Qwen3.8-Flash-Next 40 (Model card 5 of 20, intended use and context only.)
- Reach, Swift 1.5 Qwen3.8-Flash-Next +25: Inkling 2 Small 40 (Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line.); Swift 1.5 Qwen3.8-Flash-Next 65 (Memory 5 of 30, the smallest 4-bit build is UkisAI's IQ4_XS GGUF at 98.6 GB with the vision projector, 118.3 GB with a fifth, above the reference machine's GPU…)
- Agent interface, Inkling 2 Small +25: Inkling 2 Small 85 (Chat template 20, a Jinja file in the repository.); Swift 1.5 Qwen3.8-Flash-Next 60 (Chat template 20, the base's Jinja file.)
- Risk, Inkling 2 Small +20: Inkling 2 Small 65 (File safety 25, safetensors only and no repository code to run.); Swift 1.5 Qwen3.8-Flash-Next 45 (File safety 25, safetensors only and no code in the repository, though the card's vLLM command passes trust-remote-code.)