# Devstral Small 2 vs Qwen-AgentWorld-35B-A3B > Devstral Small 2 scores 61 (C) to Qwen-AgentWorld-35B-A3B's 52.1 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen-agentworld-35b-a3b - Markdown: https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen-agentworld-35b-a3b.md (~10,250 tokens) - Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: 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) - DNS: dig +short TXT .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. under the zone, and the same under grade.letme.dev) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-11-10 Devstral Small 2 scores 61 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in every scored category. Both do open-weight models you run yourself. - Devstral Small 2: grade C, 61/100, rank #60 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/devstral-small-2.md · JSON https://www.anchorterminal.com/api/v1/tools/devstral-small-2.json - Qwen-AgentWorld-35B-A3B: grade D, 52.1/100, rank #141 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen-agentworld-35b-a3b.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Devstral Small 2 (C) Good for: Developers who want a dependable local coding agent on one consumer GPU or a 32 GB Mac Ahead on: - Reach, 90 against 55 - Risk, 60 against 55 - Agent interface, 65 against 50 - Documentation and upkeep, 46 against 41 Watch for: No limitations, safety results, languages or data on the card ### Qwen-AgentWorld-35B-A3B (D) Good for: Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine Watch for: Not a general assistant, and the card doesn't describe using it to call tools ## Why the edge ### Reach: Devstral Small 2 +35 - Devstral Small 2 (90): Memory 25, the smallest build at 4 bits from a runtime's own library is Ollama's devstral-small-2 at Q4_K_M, 15 GB, and 15 GB × 1.2 = 18 GB, within 24 GB. Mistral's own FP8 files are 25.79 GB. Runtimes 25, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the mistral3 model, llama.cpp b12242 has the architecture with a GGUF from its own organisation, and Ollama's library has devstral-small-2. Builds 10, one quantised precision from Mistral, the FP8 weights it releases. Terms 15, Apache 2.0 in the card's metadata and text, an OSI licence with nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Mistral's own API serves Devstral Small 2: the card says the model is available through its API and points there when a local runtime underperforms. 25 + 25 + 10 + 15 + 10 + 5 = 90. - 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: Devstral Small 2 +15 - Devstral Small 2 (65): Chat template 20, chat_template.jinja in the repository (11,362 characters), with the tokenizer's tekken file for mistral-common. Tool-calling format 25, the card documents tools in the OpenAI function format with an example, names the mistral tool-call parser with auto tool choice for vLLM, shows the same for SGLang, and ships test prompts with the expected tool-call output. Trained tool calling 10, the card says the model excels at using tools, and its tests cover one tool call and calls made one at a time in sequence. Structured output 0, Nothing on the card about JSON or schema-constrained answers for this model. Reasoning control 0, no reasoning mode is documented, and a June 2026 commit removed stray thinking tokens from the files. Context 10, 256K tokens per the card, served at 262,144 in its vLLM command. 20 + 25 + 10 + 0 + 0 + 10 = 65. - 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. ### Risk: Devstral Small 2 +5 - Devstral Small 2 (60): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, files in Mistral's verified mistralai organisation, which Mistral's site links to per our Mistral Large 4 listing (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, mistral.ai's security.txt gives a security contact and a submission policy, as read for the Mistral Large 4 listing (5). 25 + 15 + 0 + 0 + 15 + 5 = 60. - 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. ### Documentation and upkeep: Devstral Small 2 +5 - Devstral Small 2 (46): Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the last commit, on 15 July 2026, updated the files to match mistral-common, 118 days before this check and within 180. Responsiveness 10, Of the 23 most recent discussions that aren't pull requests (9 December 2025 to 6 November 2026), 11 have a reply from a mistralai member, which is some. Version policy 5, Devstral Small 1.1 stays in its own repository, which this card links as the predecessor, with no dated note on the older card that we read. File health 10, Config, template, tokenizer and card agree, and the June and July commits fixed stray tokens and brought the files in line with mistral-common. 11 + 0 + 10 + 10 + 5 + 10 = 46. - 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. ## Score by category | Category | Weight | Devstral Small 2 | Qwen-AgentWorld-35B-A3B | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 90 | 55 | Devstral Small 2 +35 | | Risk | 20% (20 this run) | 60 | 55 | Devstral Small 2 +5 | | Agent interface | 10% (10 this run) | 65 | 50 | Devstral Small 2 +15 | | Documentation and upkeep | 10% (10 this run) | 46 | 41 | Devstral Small 2 +5 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **61 · C** | **52.1 · D** | | ## Facts side by side | Fact | Devstral Small 2 | Qwen-AgentWorld-35B-A3B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Mistral 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 | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | 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 | ## Verdicts **Devstral Small 2.** The easy one to run: a 24B coding agent under Apache 2.0 that five runtimes carry, 15 GB at 4 bits in Ollama, with a 256K context, image input and well-documented tool calling. It's eleven months old, calls tools one at a time, has no reasoning mode, and its card says nothing on limits, safety or data. **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 ### Devstral Small 2 1. `ollama run devstral-small-2` is the quickest start, at 15 GB 2. On vLLM pass `--tool-call-parser mistral --enable-auto-tool-choice` 3. Send the system prompt from CHAT_SYSTEM_PROMPT.txt in the repository. The card says results depend on it 4. Use a low temperature. The repository's default is 0.15 5. Plan for one tool call per turn 6. The same model is on our Mistral API listing if you'd rather not host it ### Qwen-AgentWorld-35B-A3B 1. 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 2. With vLLM pass `--language-model-only`, or startup fails on the missing vision weights 3. Use temperature 0.6, top_p 0.95 and top_k 20, and allow up to 32,768 output tokens, as the card recommends 4. Keep at least 128K of context, since the simulation depends on the history 5. Thinking is on by default and comes back through the qwen3 reasoning parser 6. A simulated observation is a prediction. Check anything that matters against the real environment ## Questions ### Which is better for AI agents, Devstral Small 2 or Qwen-AgentWorld-35B-A3B? Devstral Small 2 scores 61 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in every scored category. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen-agentworld-35b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen-agentworld-35b-a3b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "devstral-small-2", "b": "qwen-agentworld-35b-a3b"}`. 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How: https://www.anchorterminal.com/agents/#mcp