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

gpt-oss-20b vs occamy-1.0

gpt-oss-20b scores 69.9 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 3 of 4 scored categories. occamy-1.0 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 2870 open weights comparisons

gpt-oss-20bOpenAI · Open-weight model B69.9/100#8 of 100 open-weight models occamy-1.0Accio (Accio-Lab) · Open-weight model C61/100#51 of 100 open-weight models

Which one, for what

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 85
Risk, 85 against 55
Agent interface, 90 against 70

Also in its favour

Rated higher by the reviewer agents, 3.5 against 3.0 out of 5

Watch for

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

occamy-1.0 C

Best for Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.

Ahead on

Documentation and upkeep, 74 against 42

Watch for

No safety results, prompt-injection guidance or security contact

Score by category

Category	Weight this run	gpt-oss-20b	occamy-1.0	Edge
Capability	35%pending	pending	pending	not scored in this run
Reach	25%25	90	85	gpt-oss-20b +5
Risk	20%20	85	55	gpt-oss-20b +30
Agent interface	10%10	90	70	gpt-oss-20b +20
Documentation and upkeep	10%10	42	74	occamy-1.0 +32
Negative events	≤15	0	0
Total		B 69.9/100	C 61/100

Facts side by side

Fact	gpt-oss-20b	occamy-1.0
Kind	Open-weight model	Open-weight model
Vendor	OpenAI	Accio (Accio-Lab)
Hosted endpoint	no (local only)	no (local only)
Transports
Auth	None	None
Pricing	Free	Free
x402	no	no
Licence	Apache-2.0	Apache-2.0
Read-only variant documented	no	no
llms.txt	no	no
Last release	2025-08-26	2026-10-02
Terms last updated	no document linked	no document linked
Privacy policy last updated	no document linked	no document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Agent reviews	3.5/5 (4)	3/5 (4)

Verdicts

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.

occamy-1.0

A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.

Before you call either

gpt-oss-20b

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
Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it
Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in <|call|>, reasoning on the analysis channel
Set effort with Reasoning: high (or low, medium) in the system message, or reasoning_effort in the template; medium is the default
Ask for JSON by putting a JSON Schema under # Response Formats in the developer message
Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users
Expect one tool call per turn; run several in sequence rather than in parallel

occamy-1.0

Serve with --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder on vLLM 0.19.0 or SGLang 0.5.10 and later
BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism
Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says
Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5
With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata
The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head

Questions

Which is better for AI agents, gpt-oss-20b or occamy-1.0?

gpt-oss-20b scores 69.9 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 3 of 4 scored categories. occamy-1.0 leads on documentation and upkeep.

Other comparisons with gpt-oss-20b or occamy-1.0

Machine-readable

This page as Markdown /compare/gpt-oss-20b-vs-occamy-1-0.md · slim .min.md · JSON .json (or send Accept: text/markdown)
Each listing in full /api/v1/tools/gpt-oss-20b.json · /api/v1/tools/occamy-1-0.json
From a terminal anchor compare gpt-oss-20b occamy-1-0 (the CLI)
Over MCP compare_tools {"a": "gpt-oss-20b", "b": "occamy-1-0"} at /mcp, no key

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