Head to head · Open-weight models you run yourself · October 2026 research run
DiffusionGemma 26B A4B IT vs Qwen-AgentWorld-35B-A3B
Qwen-AgentWorld-35B-A3B and DiffusionGemma 26B A4B IT score within a point of each other on agent readiness, 52.1 (D) and 51.3 (D). DiffusionGemma 26B A4B IT leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons
Which one, for what
Best for Agents with about 64 GB of GPU memory that want fast single-user generation from text and images and can accept lower quality than Gemma 4
Ahead on
- Risk, 70 against 55
- Agent interface, 70 against 50
- Documentation and upkeep, 60 against 41
Watch for
No quantised build from Google, so the smallest official build needs the 64 GB band
Best for Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
Not a general assistant, and the card doesn't describe using it to call tools
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 DiffusionGemma 26B A4B IT +20
DiffusionGemma 26B A4B IT 70
The chat template is in the repository (20) and handles several tool calls in one turn, and the card names function calling as trained (20). The tool-calling format gets 10, since only the template and the shipped response schema say how tools work here and Google's tool-calling guide is for Gemma 4. Structured output scores 0, undocumented and rejected by SGLang. Thinking can be turned on or off per request with the reasoning in its own channel (10), and the context is 256K (10).
Qwen-AgentWorld-35B-A3B 50
Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json. Tool-calling format 10, only the template says how tools are declared and how calls come back. Trained tool calling 10, the template renders several tool_call blocks in one turn, but the card presents the model as a simulator of what tools and environments return, not as a tool caller. Structured output 0, no JSON or JSON Schema output documented for the model. Reasoning control 0, the card says thinking is on by default and names the qwen3 reasoning parser, but doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens native per the card and the text config. 20 + 10 + 10 + 0 + 0 + 10 = 50.
Documentation and upkeep DiffusionGemma 26B A4B IT +19
DiffusionGemma 26B A4B IT 60
The card covers all seven points (20), and the training data is a general description with a January 2025 cut-off (10). The files last changed on 15 July 2026, 112 days before this check (10). Google organisation members answered 10 of the 20 discussions (10). It's a first release (5). File health gets 5 because the diffusers scheduler config disagrees with the card's sampling settings, though the files on the documented path agree.
Qwen-AgentWorld-35B-A3B 41
Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length. Training data 5, A general description without a cut-off, the three training stages and a statement that no outputs from external API services were included. Last change 10, the last commit was on 25 June 2026, an update to the card, 138 days before this check, past 90 days and within 180. Responsiveness 0, 10 discussions that aren't pull requests, opened between 24 June and 5 July 2026. Version policy 5, A first release, with nothing replaced. File health 10, Config, both copies of the template and the card agree on the architecture and the context. 11 + 5 + 10 + 0 + 5 + 10 = 41.
Risk DiffusionGemma 26B A4B IT +15
DiffusionGemma 26B A4B IT 70
File safety gets the full 25, safetensors only and loaded by Transformers' own code and a Jinja template. Provenance gets 15 for files in Google's organisation with a hash for every file. Licence risk keeps 15 under plain Apache 2.0. Agent guidance gets 10 for the card's list of harm categories and its advice to add content-safety safeguards. Safety evaluation scores 0 because the card states improvements without figures. The security programme gets 5 for Google's security.txt, with no public advisories for Gemma.
Qwen-AgentWorld-35B-A3B 55
File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map. Provenance 15, files sit in the Qwen organisation, the one Alibaba's Qwen repositories on GitHub link to per the Qwen3.6-35B-A3B listing (10), and the Hub gives a SHA-256 for every large file (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, no prompt-injection guidance, instruction hierarchy, refusal statement or general cautions on the card. Licence risk 15, Apache 2.0 has no use policy, no threshold and no terms the licensor can change or revoke, and the card's licence link points at the LICENSE file in the repository. Security programme 0, no reporting route on the card. 25 + 15 + 0 + 0 + 15 + 0 = 55.
Score by category
| Category | Weight this run | DiffusionGemma 26B A4B IT | Qwen-AgentWorld-35B-A3B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 55 | 55 | even |
| Risk | 20%20 | 70 | 55 | DiffusionGemma 26B A4B IT +15 |
| Agent interface | 10%10 | 70 | 50 | DiffusionGemma 26B A4B IT +20 |
| Documentation and upkeep | 10%10 | 60 | 41 | DiffusionGemma 26B A4B IT +19 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 51.3/100 | D 52.1/100 |
Facts side by side
| Fact | DiffusionGemma 26B A4B IT | Qwen-AgentWorld-35B-A3B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | Alibaba (Qwen team) |
| 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 | yes | no |
| Last release | 2026-07-15 | 2026-06-25 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.5/5 (4) | none |
How the scores have moved
Qwen-AgentWorld-35B-A3B
No score change since it was listed.
Verdicts
DiffusionGemma 26B A4B IT
A text diffusion model for fast low-concurrency local generation from text, images and video, with optional thinking and Gemma 4's tool format, under Apache 2.0. Google's BF16 files need about 62 GB, and it runs in Transformers, SGLang and vLLM. Google's own figures put it below Gemma 4 26B A4B, and Google labels it experimental.
Qwen-AgentWorld-35B-A3B
A specialist, not a chat model. It plays the environment an agent acts in, across seven domains, so you can train or test an agent without the real thing. Alibaba ships BF16 only, which fits a 128 GB machine, and hasn't answered a discussion on it or changed the files since June.
Before you call either
DiffusionGemma 26B A4B IT
- Serve it with
sglang serve --model-path google/diffusiongemma-26B-A4B-it --dllm-algorithm Gemma4Renoise --trust-remote-codeon SGLang v0.5.22 or later, then call /v1/chat/completions - In Transformers, install
transformers>=5.11.0and loadDiffusionGemmaForBlockDiffusionwithdtype="auto"; generation_config.json already holds the recommended sampler - Turn thinking on with
enable_thinking=Truein apply_chat_template or<|think|>at the start of the system prompt, read the reasoning between<|channel>thoughtand<channel|>, and drop it from history before the next turn - Don't rely on temperature, top_p, logit_bias or JSON Schema in SGLang, which ignores or rejects them for this model; validate JSON yourself
- Streaming arrives one 256-token canvas at a time, not token by token
- Put images before text in the prompt, and pick an image token budget of 70 to 1,120 by how much detail the task needs
Qwen-AgentWorld-35B-A3B
- Use it as the environment, not the agent. Give it the domain's system prompt from Alibaba's GitHub repository, the history and the agent's action, and it returns the predicted observation
- With vLLM pass
--language-model-only, or startup fails on the missing vision weights - Use temperature 0.6, top_p 0.95 and top_k 20, and allow up to 32,768 output tokens, as the card recommends
- Keep at least 128K of context, since the simulation depends on the history
- Thinking is on by default and comes back through the qwen3 reasoning parser
- A simulated observation is a prediction. Check anything that matters against the real environment
Questions
Which is better for AI agents, DiffusionGemma 26B A4B IT or Qwen-AgentWorld-35B-A3B?
Qwen-AgentWorld-35B-A3B and DiffusionGemma 26B A4B IT score within a point of each other on agent readiness, 52.1 (D) and 51.3 (D). DiffusionGemma 26B A4B IT leads on risk, agent interface and documentation and upkeep.
Other comparisons with DiffusionGemma 26B A4B IT or Qwen-AgentWorld-35B-A3B
- Agents-A1-4B vs DiffusionGemma 26B A4B IT
- Agents-A1-4B vs Qwen-AgentWorld-35B-A3B
- Apertus v1.5 8B vs DiffusionGemma 26B A4B IT
- Apertus v1.5 8B vs Qwen-AgentWorld-35B-A3B
- Apodex-1.1-mini vs DiffusionGemma 26B A4B IT
- Apodex-1.1-mini vs Qwen-AgentWorld-35B-A3B
- Arete-27B vs DiffusionGemma 26B A4B IT
- Arete-27B vs Qwen-AgentWorld-35B-A3B
- BigBang-v1 vs DiffusionGemma 26B A4B IT
- BigBang-v1 vs Qwen-AgentWorld-35B-A3B
- Carbon-X vs DiffusionGemma 26B A4B IT
- Carbon-X vs Qwen-AgentWorld-35B-A3B
- Cosmos-Reason2-2B vs DiffusionGemma 26B A4B IT
- Cosmos-Reason2-2B vs Qwen-AgentWorld-35B-A3B
- Darwin-36B-Opus vs DiffusionGemma 26B A4B IT
- Darwin-36B-Opus vs Qwen-AgentWorld-35B-A3B
- DeepSeek-V3.2 vs DiffusionGemma 26B A4B IT
- DeepSeek-V3.2 vs Qwen-AgentWorld-35B-A3B
- DeepSeek V4.1 Flash vs DiffusionGemma 26B A4B IT
- DeepSeek V4.1 Flash vs Qwen-AgentWorld-35B-A3B
- DeepSeek-V4-Flash-0731 vs DiffusionGemma 26B A4B IT
- DeepSeek-V4-Flash-0731 vs Qwen-AgentWorld-35B-A3B
- DiffusionGemma 26B A4B IT vs Gemma 4 12B IT
- DiffusionGemma 26B A4B IT vs Gemma 4 26B A4B IT
- DiffusionGemma 26B A4B IT vs Gemma 4 31B IT
- DiffusionGemma 26B A4B IT vs Gemma 4 E2B IT
- DiffusionGemma 26B A4B IT vs Gemma 4 E4B IT
- DiffusionGemma 26B A4B IT vs GLM-4.5-Air
- DiffusionGemma 26B A4B IT vs GLM-4.7-Flash
- DiffusionGemma 26B A4B IT vs GLM-5.3
- DiffusionGemma 26B A4B IT vs GLM-5.3-Flash
- DiffusionGemma 26B A4B IT vs gpt-oss-120b
- DiffusionGemma 26B A4B IT vs gpt-oss-20b
- DiffusionGemma 26B A4B IT vs Granite 4.2 30B
- DiffusionGemma 26B A4B IT vs Granite 4.2 3B
- DiffusionGemma 26B A4B IT vs Granite 4.2 8B
- DiffusionGemma 26B A4B IT vs Hy-Memory-30B-A3B
- DiffusionGemma 26B A4B IT vs Hy3
- DiffusionGemma 26B A4B IT vs Inkling
- DiffusionGemma 26B A4B IT vs Inkling-Small
- DiffusionGemma 26B A4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview
- DiffusionGemma 26B A4B IT vs Kimi K3
- DiffusionGemma 26B A4B IT vs Kimi K3.1 Pro
- DiffusionGemma 26B A4B IT vs Kolibri-1
- DiffusionGemma 26B A4B IT vs Kronos
- DiffusionGemma 26B A4B IT vs Laguna M.1
- DiffusionGemma 26B A4B IT vs Laguna S 2.1
- DiffusionGemma 26B A4B IT vs Laguna XS 2.1
- DiffusionGemma 26B A4B IT vs LBS-27B
- DiffusionGemma 26B A4B IT vs LFM2.5-2.6B
- DiffusionGemma 26B A4B IT vs LFM3-1.7B
- DiffusionGemma 26B A4B IT vs LFM3-Audio-2B
- DiffusionGemma 26B A4B IT vs LFM3-Omni-2B
- DiffusionGemma 26B A4B IT vs LFM3-VL-2B
- DiffusionGemma 26B A4B IT vs Ling-3.0-tiny
- DiffusionGemma 26B A4B IT vs Ling-3.1-flash-1019
- DiffusionGemma 26B A4B IT vs MiMo-V2.6 Distill Qwen 9B
- DiffusionGemma 26B A4B IT vs MiniCPM-o 4.5
- DiffusionGemma 26B A4B IT vs MiniCPM-V 4.7 1B
- DiffusionGemma 26B A4B IT vs MiniCPM-V 4.7 35B-A3B
- DiffusionGemma 26B A4B IT vs MiniCPM5-2B
- DiffusionGemma 26B A4B IT vs MiniMax-M2.5
- DiffusionGemma 26B A4B IT vs MiniMax-M2.7
- DiffusionGemma 26B A4B IT vs MiniMax-M3.1-Flash
- DiffusionGemma 26B A4B IT vs Mistral Large 4
- DiffusionGemma 26B A4B IT vs Muse Glimmer 30B
- DiffusionGemma 26B A4B IT vs Nanbeige4.3-33B
- DiffusionGemma 26B A4B IT vs NVIDIA Nemotron 3.5 Bolt E4B 4GB
- DiffusionGemma 26B A4B IT vs Nemotron 3.5 Lightning 30B A3B
- DiffusionGemma 26B A4B IT vs Nemotron 3 Nano 30B A3B
- DiffusionGemma 26B A4B IT vs Nemotron 3 Nano 4B
- DiffusionGemma 26B A4B IT vs Nemotron 3 Nano Omni 30B A3B Reasoning
- DiffusionGemma 26B A4B IT vs Nemotron 3 Super 120B A12B
- DiffusionGemma 26B A4B IT vs Nemotron 3 Ultra 550B A55B
- DiffusionGemma 26B A4B IT vs occamy-1.0
- DiffusionGemma 26B A4B IT vs Olmo 3 7B Think
- DiffusionGemma 26B A4B IT vs Ornith-1.5-122B
- DiffusionGemma 26B A4B IT vs Ornith-1.5-35B-A3B
- DiffusionGemma 26B A4B IT vs Ornith-1.5-397B
- DiffusionGemma 26B A4B IT vs Ornith-1.5-9B
- DiffusionGemma 26B A4B IT vs Qwen3-30B-A3B-Instruct-2507
- DiffusionGemma 26B A4B IT vs Qwen3-4B-Instruct-2507
- DiffusionGemma 26B A4B IT vs Qwen3.5-0.8B
- DiffusionGemma 26B A4B IT vs Qwen3.5-122B-A10B
- DiffusionGemma 26B A4B IT vs Qwen3.5-2B
- DiffusionGemma 26B A4B IT vs Qwen3.5-397B-A17B
- DiffusionGemma 26B A4B IT vs Qwen3.5-4B
- DiffusionGemma 26B A4B IT vs Qwen3.5-9B
- DiffusionGemma 26B A4B IT vs Qwen3.6-27B
- DiffusionGemma 26B A4B IT vs Qwen3.6-35B-A3B
- DiffusionGemma 26B A4B IT vs Qwen3.8-27B
- DiffusionGemma 26B A4B IT vs Qwen3.8-Flash-Next
- DiffusionGemma 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-Coder-Next
- DiffusionGemma 26B A4B IT vs Qwen3-Omni-30B-A3B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-VL-2B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-VL-30B-A3B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-VL-32B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-VL-4B-Instruct
- DiffusionGemma 26B A4B IT vs Qwen3-VL-8B-Instruct
- DiffusionGemma 26B A4B IT vs Qwopus3.8-27B-Flash-V2
- DiffusionGemma 26B A4B IT vs Recursive Flint
- DiffusionGemma 26B A4B IT vs Ripple-65B Preview
- DiffusionGemma 26B A4B IT vs SmolLM3-3B
- DiffusionGemma 26B A4B IT vs Spark-X2.6-4B
- DiffusionGemma 26B A4B IT vs Swift 1.5 Qwen3.8-27B
- DiffusionGemma 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next
- DiffusionGemma 26B A4B IT vs ThinkingCap (Qwen3.8 27B)
- DiffusionGemma 26B A4B IT vs Baidu Unlimited-OCR-2
- Gemma 4 12B IT vs Qwen-AgentWorld-35B-A3B
- Gemma 4 26B A4B IT vs Qwen-AgentWorld-35B-A3B
- Gemma 4 31B IT vs Qwen-AgentWorld-35B-A3B
- Gemma 4 E2B IT vs Qwen-AgentWorld-35B-A3B
- Gemma 4 E4B IT vs Qwen-AgentWorld-35B-A3B
- GLM-4.5-Air vs Qwen-AgentWorld-35B-A3B
- GLM-4.7-Flash vs Qwen-AgentWorld-35B-A3B
- GLM-5.3-Flash vs Qwen-AgentWorld-35B-A3B
- GLM-5.3 vs Qwen-AgentWorld-35B-A3B
- gpt-oss-120b vs Qwen-AgentWorld-35B-A3B
- gpt-oss-20b vs Qwen-AgentWorld-35B-A3B
- Granite 4.2 30B vs Qwen-AgentWorld-35B-A3B
- Granite 4.2 3B vs Qwen-AgentWorld-35B-A3B
- Granite 4.2 8B vs Qwen-AgentWorld-35B-A3B
- Hy-Memory-30B-A3B vs Qwen-AgentWorld-35B-A3B
- Hy3 vs Qwen-AgentWorld-35B-A3B
- Inkling-Small vs Qwen-AgentWorld-35B-A3B
- Inkling vs Qwen-AgentWorld-35B-A3B
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen-AgentWorld-35B-A3B
- Kimi K3.1 Pro vs Qwen-AgentWorld-35B-A3B
- Kimi K3 vs Qwen-AgentWorld-35B-A3B
- Kolibri-1 vs Qwen-AgentWorld-35B-A3B
- Kronos vs Qwen-AgentWorld-35B-A3B
- Laguna M.1 vs Qwen-AgentWorld-35B-A3B
- Laguna S 2.1 vs Qwen-AgentWorld-35B-A3B
- Laguna XS 2.1 vs Qwen-AgentWorld-35B-A3B
- LBS-27B vs Qwen-AgentWorld-35B-A3B
- LFM2.5-2.6B vs Qwen-AgentWorld-35B-A3B
- LFM3-1.7B vs Qwen-AgentWorld-35B-A3B
- LFM3-Audio-2B vs Qwen-AgentWorld-35B-A3B
- LFM3-Omni-2B vs Qwen-AgentWorld-35B-A3B
- LFM3-VL-2B vs Qwen-AgentWorld-35B-A3B
- Ling-3.0-tiny vs Qwen-AgentWorld-35B-A3B
- Ling-3.1-flash-1019 vs Qwen-AgentWorld-35B-A3B
- MiMo-V2.6 Distill Qwen 9B vs Qwen-AgentWorld-35B-A3B
- MiniCPM-o 4.5 vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 1B vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 35B-A3B vs Qwen-AgentWorld-35B-A3B
- MiniCPM5-2B vs Qwen-AgentWorld-35B-A3B
- MiniMax-M2.5 vs Qwen-AgentWorld-35B-A3B
- MiniMax-M2.7 vs Qwen-AgentWorld-35B-A3B
- MiniMax-M3.1-Flash vs Qwen-AgentWorld-35B-A3B
- Mistral Large 4 vs Qwen-AgentWorld-35B-A3B
- Muse Glimmer 30B vs Qwen-AgentWorld-35B-A3B
- Nanbeige4.3-33B vs Qwen-AgentWorld-35B-A3B
- NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Qwen-AgentWorld-35B-A3B
- Nemotron 3.5 Lightning 30B A3B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano 30B A3B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano 4B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Super 120B A12B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Ultra 550B A55B vs Qwen-AgentWorld-35B-A3B
- occamy-1.0 vs Qwen-AgentWorld-35B-A3B
- Olmo 3 7B Think vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-122B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-35B-A3B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-397B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-9B vs Qwen-AgentWorld-35B-A3B
- Qwen-AgentWorld-35B-A3B vs Qwen3-30B-A3B-Instruct-2507
- Qwen-AgentWorld-35B-A3B vs Qwen3-4B-Instruct-2507
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-0.8B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-122B-A10B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-2B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-397B-A17B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-4B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-9B
- Qwen-AgentWorld-35B-A3B vs Qwen3.6-27B
- Qwen-AgentWorld-35B-A3B vs Qwen3.6-35B-A3B
- Qwen-AgentWorld-35B-A3B vs Qwen3.8-27B
- Qwen-AgentWorld-35B-A3B vs Qwen3.8-Flash-Next
- Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-Next
- Qwen-AgentWorld-35B-A3B vs Qwen3-Omni-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-2B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-32B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-4B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-8B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwopus3.8-27B-Flash-V2
- Qwen-AgentWorld-35B-A3B vs Recursive Flint
- Qwen-AgentWorld-35B-A3B vs Ripple-65B Preview
- Qwen-AgentWorld-35B-A3B vs SmolLM3-3B
- Qwen-AgentWorld-35B-A3B vs Spark-X2.6-4B
- Qwen-AgentWorld-35B-A3B vs Swift 1.5 Qwen3.8-27B
- Qwen-AgentWorld-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next
- Qwen-AgentWorld-35B-A3B vs ThinkingCap (Qwen3.8 27B)
- Qwen-AgentWorld-35B-A3B vs Baidu Unlimited-OCR-2
Machine-readable
- This page as Markdown
/compare/diffusiongemma-26b-a4b-it-vs-qwen-agentworld-35b-a3b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/diffusiongemma-26b-a4b-it.json·/api/v1/tools/qwen-agentworld-35b-a3b.json - From a terminal
anchor compare diffusiongemma-26b-a4b-it qwen-agentworld-35b-a3b(the CLI) - Over MCP
compare_tools {"a": "diffusiongemma-26b-a4b-it", "b": "qwen-agentworld-35b-a3b"}at/mcp, no key