Head to head · Open-weight models you run yourself · October 2026 research run
Cola2 vs Swift 1.5 Qwen3.8-27B
Swift 1.5 Qwen3.8-27B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
Cola2 F
Best for Researchers working on latent or diffusion language models who want a checkpoint to study
Ahead on
- Documentation and upkeep, 58 against 43
Watch for
No licence stated for the weights
Best for Agents on a 24 to 32 GB GPU or Mac that want Qwen3.8-27B's skills with shorter thinking, for teams under US$1M revenue or research.
Ahead on
- Reach, 80 against 25
- Risk, 50 against 40
- Agent interface, 60 against 20
Watch for
Commercial use above US$1M gross annual revenue needs a separate licence
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reach Swift 1.5 Qwen3.8-27B +55
Cola2 25
Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB. Loaded as BF16, as the card's example does, it needs about half, but the line reads the file size. Runtimes 0, none of the six runs it in a released version. Builds 0, one set of weights and no quantised build. Terms 0, no licence for the weights. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and nothing names an API that serves it. 15 + 0 + 0 + 0 + 10 + 0 = 25.
Swift 1.5 Qwen3.8-27B 80
Memory 25 of 30, UkisAI's 4-bit MLX build is 15.9 GB and its 4-bit GGUF with the vision projector 16.4 GB, both under 20 GB with a fifth added, which fits 24 GB. Runtimes 20, the architecture is Qwen3.8-27B's, which released llama.cpp, vLLM, SGLang and Transformers run, while Ollama's entry is the base's. Builds 15, GGUF, INT4, NVFP4, FP8 and MLX builds from UkisAI. Terms 10, a custom licence that is free for commercial use below US$1M revenue. Download 10, not gated. Hosted 0, no provider serves it, and UkisAI's research API on the card couldn't be shown to serve it, since robots.txt disallows calling it.
Agent interface Swift 1.5 Qwen3.8-27B +40
Cola2 20
Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer. Tool-calling format 0, none. Trained tool calling 0, not trained for tool calling. Structured output 0, Nothing about JSON or schema-constrained output. Reasoning control 0, no reasoning mode. Context 0, no context length is stated. 20 + 0 + 0 + 0 + 0 + 0 = 20.
Swift 1.5 Qwen3.8-27B 60
Chat template 20, the base's Jinja file. Tool-calling format 10 of 25, the format is only in the template and the parser only in serving commands. Trained tool calling 20, several calls a turn and agentic post-training. Structured output 0, not documented. Reasoning control 0, the card mentions reasoning_effort but not how to set it, turn thinking off or read the reasoning. Context 10, 262,144 tokens native.
Documentation and upkeep Cola2 +15
Cola2 58
Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model card it links. Training data 15, the GitHub model card names the source (OLMo 2 pretraining text, retokenised) and the mix by stage with token counts, 346.03B in all. Last change 20, All six commits are from 6 November 2026, four days before this check, the last one updating a checksum in the README. Responsiveness 0, no discussions on the repository, so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 5, A first release. File health 10, Config, files and card agree: F32 weights, a float32 config and a card that says to load them as bfloat16, with SHA256SUMS to check the download. 8 + 15 + 20 + 0 + 5 + 10 = 58.
Swift 1.5 Qwen3.8-27B 43
Model card 8 of 20, intended use, parameters and context only. Training data 5, a general description with no cut-off. Last change 20, UkisAI's own ONNX builds of the model took a new card and licence on 8 October, 26 days ago (the main repository's last commit is the 3 October README update). Responsiveness 0, UkisAI answered none of 8 discussions. Version policy 5, Swift 1.0 stays in its own repository without a note. File health 5, reports of a broken model wait without a reply and the card's metadata claims a gate that doesn't exist.
Risk Swift 1.5 Qwen3.8-27B +10
Cola2 40
File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ByteDance-Seed organisation, which the ByteDance-Seed GitHub repository for the model links to (10). Safety evaluation 0, no safety results. Agent guidance 5, General cautions in the GitHub model card: not instruction-tuned or safety-aligned, not for use as an assistant, for facts or advice, or for high-impact decisions about people. Licence risk 0, With no licence for the weights there is nothing to hold ByteDance to. Security programme 5, the GitHub repository's SECURITY.md sends reports to ByteDance's security centre and says how they're assessed (5). 15 + 15 + 0 + 5 + 0 + 5 = 40.
Swift 1.5 Qwen3.8-27B 50
File safety 25, safetensors only and nothing from the repository runs. Provenance 15, the files are in the account UkisAI's site links to, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 0, nothing on prompt injection, refusals or safeguards. Licence risk 10, a revenue threshold. Security programme 0, no way to report a flaw was found.
Score by category
| Category | Weight this run | Cola2 | Swift 1.5 Qwen3.8-27B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 25 | 80 | Swift 1.5 Qwen3.8-27B +55 |
| Risk | 20%20 | 40 | 50 | Swift 1.5 Qwen3.8-27B +10 |
| Agent interface | 10%10 | 20 | 60 | Swift 1.5 Qwen3.8-27B +40 |
| Documentation and upkeep | 10%10 | 58 | 43 | Cola2 +15 |
| Negative events | ≤15 | 0 | 0 | |
| Total | F 33.9/100 | C 61/100 |
Facts side by side
| Fact | Cola2 | Swift 1.5 Qwen3.8-27B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | ByteDance (Seed) | UkisAI |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | None stated for the weights (the code is 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 with a separate Swift Enterprise License above it. Built on Qwen3.8-27B, whose Apache 2.0 still governs the base |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-06 | 2026-09-24 |
| Terms last updated | no document linked | no date given |
| Privacy policy last updated | no document linked | no document linked |
| 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 | 2.3/5 (4) |
Verdicts
Cola2
A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.
Swift 1.5 Qwen3.8-27B
A Qwen3.8-27B cousin post-trained to think in fewer tokens, for coding and agent work with images in, that fits a 24 GB machine with UkisAI's own 4-bit builds. Commercial use is free only below US$1M revenue. The main risks are that nobody at UkisAI answers its discussions, and that the shorter thinking rests on UkisAI's own benchmarks.
Before you call either
Cola2
- Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions
- Don't use it commercially on the strength of this listing. The weights have no stated licence
- If you study it, read modeling_cola2.py first: trust_remote_code runs it
- Pin Transformers below 5, as the card requires
- Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding
- Check the download with
sha256sum -c SHA256SUMS
Swift 1.5 Qwen3.8-27B
- Quickest start is
llama-server -hf ukisai/Swift-1.5-Qwen3.8-27B-GGUF:Q4_K_M --jinja, about 18.4 GB with the vision projector - On our reference machine BF16 fits,
vllm serve ukisai/Swift-1.5-Qwen3.8-27b --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder - The template is Qwen3.8-27B's, so
chat_template_kwargswithreasoning_effortlow, medium or xhigh (default) andenable_thinkingfalse work as on the base - UkisAI benchmarked it at temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 0, which is a reasonable starting point
- The MLX 4-bit build needs UkisAI's patched MLX-LM and has no image or video chat
- Check the licence before commercial use, it stops at US$1M gross annual revenue including affiliates
- MTP self-speculative decoding is available with the base's head, flags on the card
Questions
Which is better for AI agents, Cola2 or Swift 1.5 Qwen3.8-27B?
Swift 1.5 Qwen3.8-27B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.
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- Spark-X2.6-4B vs Swift 1.5 Qwen3.8-27B
- Step 3.7 Flash vs Swift 1.5 Qwen3.8-27B
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- Swift 1.5 Qwen3.8-27B vs ThinkingCap (Qwen3.8 27B)
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- Swift 1.5 Qwen3.8-27B vs WeVisOne-VL-2B
- Swift 1.5 Qwen3.8-27B vs WeVisOne-VL-4B
- Swift 1.5 Qwen3.8-27B vs ZAYA1-8B
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anchor compare cola2 swift-1-5-qwen3-8-27b(the CLI) - Over MCP
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