Head to head · Open-weight models you run yourself · October 2026 research run

Cola2 vs gpt-oss-20b

gpt-oss-20b scores 69.9 (B) 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 42

Watch for

No licence stated for the weights

gpt-oss-20b B

Best for Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time

Ahead on

  • Reach, 90 against 25
  • Risk, 85 against 40
  • Agent interface, 90 against 20

Watch for

No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered

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.

Agent interface gpt-oss-20b +70

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.

gpt-oss-20b 90

The chat template earns 20, a Jinja file in the repository. The tool-calling format earns 25, since OpenAI's harmony guide says how functions are declared and how calls come back, and OpenAI ships the openai-harmony parser. Trained tool calling earns 10, because each call ends the message and waits for its result, so it makes one call at a time. Structured output earns 15 for a JSON Schema given in the developer message, documented in the harmony guide. Reasoning control earns 10, with low, medium or high effort per request and the reasoning on its own channel, though it can't be switched off. Context earns 10 for 131,072 tokens, which OpenAI describes as trained in even though the config reaches it with YaRN.

Reach gpt-oss-20b +65

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.

gpt-oss-20b 90

Memory earns 25, since OpenAI's own MXFP4 build is 13.76 GB and a fifth on top is 16.5 GB, just past the 16 GB band, and Ollama's 14 GB build lands in the same 24 GB band. Runtimes earn the full 25 from model code in released Transformers, vLLM and SGLang, the architecture in llama.cpp and the model in Ollama's library. Builds earn 10, because OpenAI ships one quantised precision, MXFP4, and the original and metal folders are the same weights for its reference code. Terms earn 15 for Apache 2.0, whose usage policy only asks users to follow the law. Download earns 10, since the repository isn't gated. Hosted earns 5, with five inference providers live for it on its Hugging Face page on 1 November 2026, while OpenAI's own API lists it with no usable rate limit and isn't counted.

Risk gpt-oss-20b +45

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.

gpt-oss-20b 85

File safety earns 25, since the weights are safetensors and metal/model.bin is OpenAI's own raw Metal format rather than pickle, and nothing in the repository runs as code (a judgement call on the .bin name). Provenance earns 15, files in OpenAI's own organisation and a checksum on every file. Safety evaluation earns 10, because the published safety results for this size are OpenAI's own, and the outside review covered gpt-oss-120b. Agent guidance earns 15 for an instruction hierarchy the model was trained to follow, with prompt-injection results, though OpenAI reports it trails o4-mini there. Licence risk keeps 15, with nothing to deduct under Apache 2.0. The security programme earns 5 for OpenAI's security.txt with a Bugcrowd contact. Public advisories for the gpt-oss code couldn't be checked, so that half scores as absent.

Documentation and upkeep Cola2 +16

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.

gpt-oss-20b 42

The model card earns 17, covering six of the seven points and missing a statement of supported languages. Training data earns 10, a general description with a June 2024 cut-off and no sources or mix. Last change earns 5, because the files haven't changed since August 2025 and the reference code and harmony parser last changed on 1 and 5 November 2025, still within a year on 1 November 2026, while this year's commits only touch the browser tool, CI and a version number. Responsiveness earns 0, with no OpenAI reply to any of the 40 most recent discussions and none at all since August 2025. Version policy earns 5 for a first release kept in its own repository. File health earns 5, since template reports and an install report wait without a reply.

Score by category

CategoryWeight this runCola2gpt-oss-20bEdge
Capability35%pendingpendingpendingnot scored in this run
Reach25%252590gpt-oss-20b +65
Risk20%204085gpt-oss-20b +45
Agent interface10%102090gpt-oss-20b +70
Documentation and upkeep10%105842Cola2 +16
Negative events≤1500
TotalF 33.9/100B 69.9/100

Facts side by side

FactCola2gpt-oss-20b
KindOpen-weight modelOpen-weight model
VendorByteDance (Seed)OpenAI
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceNone stated for the weights (the code is Apache 2.0)Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-11-062025-08-26
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Agent reviewsnone3.5/5 (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.

gpt-oss-20b

gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.

Before you call either

Cola2

  1. Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions
  2. Don't use it commercially on the strength of this listing. The weights have no stated licence
  3. If you study it, read modeling_cola2.py first: trust_remote_code runs it
  4. Pin Transformers below 5, as the card requires
  5. Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding
  6. Check the download with sha256sum -c SHA256SUMS

gpt-oss-20b

  1. Start it with ollama run gpt-oss:20b (the build that fits the reference machine), or vllm serve openai/gpt-oss-20b with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel
  2. Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it
  3. Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in <|call|>, reasoning on the analysis channel
  4. Set effort with Reasoning: high (or low, medium) in the system message, or reasoning_effort in the template; medium is the default
  5. Ask for JSON by putting a JSON Schema under # Response Formats in the developer message
  6. Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users
  7. Expect one tool call per turn; run several in sequence rather than in parallel

Questions

Which is better for AI agents, Cola2 or gpt-oss-20b?

gpt-oss-20b scores 69.9 (B) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.

Other comparisons with Cola2 or gpt-oss-20b

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