# Swift 1.5 Qwen3.8-Flash-Next vs ZAYA1-8B (slim)

> ZAYA1-8B scores 61 (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: 2026-11-10
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ZAYA1-8B scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 54.2 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Swift 1.5 Qwen3.8-Flash-Next: C 54.2, rank #132 of 160 open-weight models · https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.min.md
- ZAYA1-8B: C 61, rank #85 of 160 open-weight models · https://www.anchorterminal.com/tools/zaya1-8b.min.md
- 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.
- ZAYA1-8B, good for People who want a small, fast reasoning model for maths and code and can live without tool calling Ahead on Reach, 80 against 65; Risk, 55 against 45; Documentation and upkeep, 50 against 40.

| Category | Swift 1.5 Qwen3.8-Flash-Next | ZAYA1-8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 80 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 40 | 50 |

| Fact (where they differ) | Swift 1.5 Qwen3.8-Flash-Next | ZAYA1-8B |
| --- | --- | --- |
| Vendor | UkisAI | Zyphra |
| Licence | 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 | Apache-2.0 |
| Last release | 2026-09-24 | 2026-07-02 |
| Terms last updated | no date given | no document linked |
| Customer content may train models | not found in the text | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | 1.8/5 (4) | none |

Why the edge:
- Reach, ZAYA1-8B +15: 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…); ZAYA1-8B 80 (Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB.)
- Risk, ZAYA1-8B +10: 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.); ZAYA1-8B 55 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Documentation and upkeep, ZAYA1-8B +10: Swift 1.5 Qwen3.8-Flash-Next 40 (Model card 5 of 20, intended use and context only.); ZAYA1-8B 50 (Model card 5, Intended use and the parameter counts are on the card.)