# Olmo 3 7B Think vs Qwen3.5-9B > Qwen3.5-9B scores 60.5 (C) to Olmo 3 7B Think's 52.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b - Markdown: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.md (~6,000 tokens) - Slim: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-10-21 Qwen3.5-9B scores 60.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on risk and documentation and upkeep. Both do open-weight models you run yourself. - Olmo 3 7B Think: grade D, 52.3/100, rank #86 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/olmo-3-7b-think.md · JSON https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json - Qwen3.5-9B: grade C, 60.5/100, rank #53 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-9b.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Olmo 3 7B Think (D) Good for: Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand Ahead on: - Risk, 75 against 55 - Documentation and upkeep, 52 against 34 Watch for: Not trained for tool calling, and the tool format lives only in the template ### Qwen3.5-9B (C) Good for: Agents that want a small multimodal tool-calling cousin on a laptop or a 16 GB GPU, under a plain licence Ahead on: - Capability, 51 against 28 - Reach, 85 against 75 - Agent interface, 70 against 35 Watch for: No quantised build from Qwen itself ## Score by category | Category | Weight | Olmo 3 7B Think | Qwen3.5-9B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 28 | 51 | Qwen3.5-9B +23 | | Reach | 25% (25 this run) | 75 | 85 | Qwen3.5-9B +10 | | Risk | 20% (20 this run) | 75 | 55 | Olmo 3 7B Think +20 | | Agent interface | 10% (10 this run) | 35 | 70 | Qwen3.5-9B +35 | | Documentation and upkeep | 10% (10 this run) | 52 | 34 | Olmo 3 7B Think +18 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **52.3 · D** | **60.5 · C** | | ## Facts side by side | Fact | Olmo 3 7B Think | Qwen3.5-9B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Ai2 (Allen Institute for AI) | 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, with Ai2's Responsible Use Guidelines named on the card | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-06-25 | 2026-03-02 | | Terms last updated | | no document linked | | Privacy policy last updated | | 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 | 2.8/5 (4) | 2.5/5 (4) | ## Verdicts **Olmo 3 7B Think.** A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions. **Qwen3.5-9B.** A small dense vision-language cousin with trained tool calling, switchable thinking and a 262,144-token context, for local agent subtasks. Ollama's 4-bit build needs about 8 GB and the BF16 files about 24 GB, in every major runtime. The main risk is neglect, with no file changes since March, no replies from Qwen to reports and no safety results. ## Before you call either ### Olmo 3 7B Think 1. Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB 2. With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend 3. Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long 4. Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags 5. Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available 6. For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling 7. A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens 8. Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research ### Qwen3.5-9B 1. Smallest start is `ollama run qwen3.5:9b` (6.6 GB, q4_k_m) 2. On vLLM run `vllm serve Qwen/Qwen3.5-9B --port 8000 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, or tool calls come back as text 3. Tool calls use the XML style ``, not Hermes JSON, so use the qwen3_coder parser and not hermes 4. Thinking is on by default; pass `chat_template_kwargs` with `enable_thinking` false for short tasks, since `/nothink` isn't supported 5. There's no generation_config.json, so pass sampling yourself, temperature 1.0, top_p 0.95, top_k 20, presence_penalty 1.5 when thinking, or 0.7, 0.8, 20, 1.5 without 6. Keep at least 128K of context when thinking, and turn on YaRN only beyond 262,144 tokens 7. Validate JSON output yourself or use the runtime's guided decoding ## Questions ### Which is better for AI agents, Olmo 3 7B Think or Qwen3.5-9B? Qwen3.5-9B scores 60.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on risk and documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "olmo-3-7b-think", "b": "qwen3-5-9b"}`. 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