Head to head · Open-weight models you run yourself · October 2026 research run
Cola2 vs Darwin-36B-Opus
Darwin-36B-Opus scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in every scored category. 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
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No licence stated for the weights
Best for Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required
Ahead on
- Reach, 80 against 25
- Risk, 55 against 40
- Agent interface, 70 against 20
Watch for
The merge method is proprietary and the current weights include an undescribed targeted refinement
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 Darwin-36B-Opus +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.
Darwin-36B-Opus 80
Memory 20, the publisher's Q4_K_M GGUF is 21.2 GB and needs about 25.4 GB with the fifth added, so 32 GB. Runtimes 20, the text-only Qwen3.5 MoE class runs in released vLLM, SGLang, Transformers and llama.cpp, while Ollama's and LM Studio's entries are the base's, not this model's. Builds 15, FINAL-Bench's POCKET-35B-GGUF has it at four precisions. Terms 15, Apache 2.0 with nothing added, with a LICENSE file since 1 November 2026, and Apache 2.0 on the base Qwen3.6-35B-A3B too. Download 10, nothing is gated. Hosted 0, no provider or API serves it.
Agent interface Darwin-36B-Opus +50
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.
Darwin-36B-Opus 70
Chat template 20, Qwen3.6's Jinja template in the repository. Tool-calling format 10, the format is only in the template and the card says nothing about tools. Trained tool calling 20, inherited from the base that was trained for it, with several calls in one turn in the template, though the publisher neither claims nor tests it. Structured output 0. Reasoning control 10, the template turns thinking off per request and the card shows where the reasoning comes back. Context 10, 262,144 tokens.
Risk Darwin-36B-Opus +15
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.
Darwin-36B-Opus 55
File safety 25, safetensors and GGUF only with no code in the repository, so the card's trust_remote_code flag loads nothing extra. Provenance 15, the files are in the FINAL-Bench organisation that vidraft.net links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published. Licence risk 15, Apache 2.0 through the whole chain with no conditions added. Security programme 0, no security.txt, policy or contact.
Score by category
| Category | Weight this run | Cola2 | Darwin-36B-Opus | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 25 | 80 | Darwin-36B-Opus +55 |
| Risk | 20%20 | 40 | 55 | Darwin-36B-Opus +15 |
| Agent interface | 10%10 | 20 | 70 | Darwin-36B-Opus +50 |
| Documentation and upkeep | 10%10 | 58 | 61 | Darwin-36B-Opus +3 |
| Negative events | ≤15 | 0 | 0 | |
| Total | F 33.9/100 | C 61/100 |
Facts side by side
| Fact | Cola2 | Darwin-36B-Opus |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | ByteDance (Seed) | FINAL-Bench (VIDRAFT) |
| 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) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-06 | 2026-04-23 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 2.5/5 (4) |
How the scores have moved
Cola2
No score change since it was listed.
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.
Darwin-36B-Opus
A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.
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
Darwin-36B-Opus
- Quickest start is
llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja, about 21 GB of files - On the reference machine BF16 fits,
vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder, the parsers for Qwen3.6's format - Thinking is on by default, send
chat_template_kwargswithenable_thinkingfalse for short tasks, a switch the card doesn't mention - The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces
- generation_config.json stops only on the end-of-text token, so add
<|im_end|>as a stop token if a runtime keeps generating after the turn ends - Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files
- Validate JSON output yourself, since structured output isn't documented
Questions
Which is better for AI agents, Cola2 or Darwin-36B-Opus?
Darwin-36B-Opus scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in every scored category.
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Machine-readable
- This page as Markdown
/compare/cola2-vs-darwin-36b-opus.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/cola2.json·/api/v1/tools/darwin-36b-opus.json - From a terminal
anchor compare cola2 darwin-36b-opus(the CLI) - Over MCP
compare_tools {"a": "cola2", "b": "darwin-36b-opus"}at/mcp, no key