Head to head · Open-weight models you run yourself · October 2026 research run
InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen-AgentWorld-35B-A3B
InternVL3.5-GPT-OSS-20B-A4B-Preview scores 53.2 (D) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 1 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on 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 6359 open weights comparisons
Which one, for what
InternVL3.5-GPT-OSS-20B-A4B-Preview D
Best for Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.
Ahead on
- Reach, 65 against 55
Watch for
No quantised build from OpenGVLab, so about 51 GB at BF16
Best for Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine
Ahead on
- Agent interface, 50 against 45
- Documentation and upkeep, 41 against 28
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.
Documentation and upkeep Qwen-AgentWorld-35B-A3B +13
InternVL3.5-GPT-OSS-20B-A4B-Preview 28
Model card 8 of 20, the family card misses limitations, context, languages and a cut-off. Training data 5, described without a cut-off. Last change 0, the last commit to either repository is 8 September 2025 and to OpenGVLab's reference code 22 September 2025, over a year before 4 November 2026. Responsiveness 10, OpenGVLab answered 3 of 8 questions across the two repositories, none since September 2025. Version policy 5, a first release. File health 0, the template uses markers the tokenizer doesn't have and contradicts the twin's template, and the card names the wrong language model in its licence line.
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.
Reach InternVL3.5-GPT-OSS-20B-A4B-Preview +10
InternVL3.5-GPT-OSS-20B-A4B-Preview 65
Memory 15 of 30, the only builds are BF16 at 42.5 GB by the repository's safetensors index, or 51 GB with a fifth added, which fits 64 GB. Runtimes 25, Transformers and vLLM load this repository, and SGLang, llama.cpp and Ollama (through llama.cpp b11963, which Ollama v0.40.14 pins) run the same weights in their GitHub format. Builds 0, OpenGVLab publishes no quantised build. Terms 15, Apache 2.0 with nothing added by the bases. Download 10, not gated. Hosted 0, no provider serves it.
Qwen-AgentWorld-35B-A3B 55
Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share. Runtimes 20, Four released runtimes run the architecture, vLLM 0.33.0 (Qwen3_5MoeForConditionalGeneration), SGLang 0.5.23, Transformers 5.22.2 (qwen3_5_moe) and llama.cpp b12242 (its Qwen conversion code). Builds 0, Alibaba publishes the BF16 weights only. Terms 15, Apache 2.0, an OSI licence, in the metadata and as a LICENSE file, with no use policy or other terms added. Download 10, the repository isn't gated, so the files download with no account and no terms to accept. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026). 10 + 20 + 0 + 15 + 10 + 0 = 55.
Agent interface Qwen-AgentWorld-35B-A3B +5
InternVL3.5-GPT-OSS-20B-A4B-Preview 45
Chat template 20, a Jinja file in the repository, though it doesn't match the tokenizer. Tool-calling format 10 of 25, only the twin's inherited harmony template mentions tools. Trained tool calling 0, no evidence it was trained to call tools. Structured output 0. Reasoning control 10, a system prompt turns thinking on and the card says the reasoning comes back in think tags. Context 5, trained at 32K tokens.
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.
Score by category
| Category | Weight this run | InternVL3.5-GPT-OSS-20B-A4B-Preview | Qwen-AgentWorld-35B-A3B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 55 | InternVL3.5-GPT-OSS-20B-A4B-Preview +10 |
| Risk | 20%20 | 55 | 55 | even |
| Agent interface | 10%10 | 45 | 50 | Qwen-AgentWorld-35B-A3B +5 |
| Documentation and upkeep | 10%10 | 28 | 41 | Qwen-AgentWorld-35B-A3B +13 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 53.2/100 | D 52.1/100 |
Facts side by side
| Fact | InternVL3.5-GPT-OSS-20B-A4B-Preview | Qwen-AgentWorld-35B-A3B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | 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; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-09-08 | 2026-06-25 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 1.8/5 (4) | none |
How the scores have moved
Qwen-AgentWorld-35B-A3B
No score change since it was listed.
Verdicts
InternVL3.5-GPT-OSS-20B-A4B-Preview
An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.
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
InternVL3.5-GPT-OSS-20B-A4B-Preview
- Serve with
vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768, which is our command; the card gives none for vLLM - Check the rendered prompt before relying on it, since the shipped template's <|im_start|> markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative
- Use Transformers 4.55.0 or later, as the card requires for this size
- For thinking, send the card's thinking system prompt and parse the reasoning out of the <think> tags, with temperature 0.6 and sampling on as the card advises
- Keep inputs within 32K tokens, the length it was trained at, whatever the config says
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, InternVL3.5-GPT-OSS-20B-A4B-Preview or Qwen-AgentWorld-35B-A3B?
InternVL3.5-GPT-OSS-20B-A4B-Preview scores 53.2 (D) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 1 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on agent interface and documentation and upkeep.
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- 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 SenseNova-Loop-9B-Preview
- Qwen-AgentWorld-35B-A3B vs SmolLM3-3B
- Qwen-AgentWorld-35B-A3B vs Spark-X2.6-4B
- Qwen-AgentWorld-35B-A3B vs Step 3.7 Flash
- 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
- Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-2B
- Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-4B
- Qwen-AgentWorld-35B-A3B vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen-agentworld-35b-a3b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json·/api/v1/tools/qwen-agentworld-35b-a3b.json - From a terminal
anchor compare internvl3-5-gpt-oss-20b-a4b-preview qwen-agentworld-35b-a3b(the CLI) - Over MCP
compare_tools {"a": "internvl3-5-gpt-oss-20b-a4b-preview", "b": "qwen-agentworld-35b-a3b"}at/mcp, no key