--- license: cc-by-4.0 language: - en - de pretty_name: "Tryouts - which open model should my research agent use?" task_categories: - question-answering tags: - agents - deep-research - tool-use - mcp - evaluation - nebius - tavily - nemotron size_categories: - n<1K configs: - config_name: hard_multihop data_files: data/hard_multihop.jsonl - config_name: own_logs data_files: data/own_logs.jsonl - config_name: tool_use data_files: data/tool_use.jsonl - config_name: single_facts data_files: data/single_facts.jsonl - config_name: results_hard_multihop data_files: results/hard_multihop.jsonl - config_name: results_hard_multihop_run2 data_files: results/hard_multihop_run2.jsonl - config_name: results_own_logs data_files: results/own_logs.jsonl - config_name: results_own_logs_deep data_files: results/own_logs_deep.jsonl - config_name: results_tool_use data_files: results/tool_use.jsonl - config_name: results_single_facts data_files: results/single_facts.jsonl --- # Tryouts Evaluation sets and full run logs for one question: **which open model should a web research agent use?** The same agent (same prompts, same Tavily search) ran across the open models on [Nebius Token Factory](https://tokenfactory.nebius.com) and Claude Opus 5 as the baseline. Code to rerun everything on your own questions: https://github.com/Malek1414/tryouts. Leaderboard: https://huggingface.co/spaces/nebius-build-week/tryouts. Built at the Nebius Build Week hackathon with NVIDIA, Berlin, 18 October 2026, by team Starke Ameisen. ## Sets | Config | Items | What it tests | |---|---:|---| | `single_facts` | 50 | Verified single facts in German and English. Every model answers from the same Tavily results. | | `hard_multihop` | 40 | Questions from [FRAMES](https://huggingface.co/datasets/google/frames-benchmark) (numerical, temporal, multiple constraints) that chain 2 to 5 facts. Each model plans its own searches, up to 3 rounds. | | `own_logs` | 16 | Written from research our own agents ran in the last month (Nightcrawler and Searchify). Each answer is backed by a verbatim quote checked against the page, and some questions rest on a false premise, so the right answer is "unknown". | | `own_logs_deep` (results only) | 16 | The own-logs questions in deep mode: full pages, Searchify's reranker (`cross-encoder/mmarco-mMiniLMv2-L12-H384-v1`), one query per fact and a quote gate. | | `tool_use` | 14 | The model drives real MCP servers through tool calls: Tavily search, extract, map and crawl; semble code search on GitHub; a headless Chrome for pages that only render with JavaScript. Gold answers were checked against the source on 18 October 2026. | Fields: `question`, `answer` (gold), `aliases`, `answer_type` (`exact`, `number`, `unanswerable`), `source`, and for `tool_use` the intended `tool`. The `results_*` configs hold every run: answer, verdict, search queries or tool calls, sources, tokens, cost in USD and seconds. The exact Tavily results every model read are in `search_cache/tavily_cache.jsonl`: drop it into the repo's `results/` folder and a rerun replays the same searches without spending credits. ## Scoring Verdicts follow SimpleQA: `correct`, `incorrect` (a wrong answer given with confidence) and `not_attempted` (the model said it could not find it). On `unanswerable` items only "unknown" is correct. Numbers allow 1% tolerance. Anything a rule cannot settle goes to a fixed judge model (Kimi K2.6) that is not a contestant. Accuracy intervals are bootstrap 95% intervals (10,000 resamples). The pick is the cheapest model whose accuracy is not credibly more than 10 points below the best one. ## Results (18 October 2026) | Model | Single facts | Hard multi-hop | Our own logs | Tool use (MCP) | $ / question (hard) | |---|---:|---:|---:|---:|---:| | Claude Opus 5 | 100% (100%–100%), 0% wrong | **88%** (78%–98%), 12% wrong | 69% (44%–88%), 19% wrong | 100% (100%–100%), 0% wrong | $0.0619 | | Reflection Beam | 100% (100%–100%), 0% wrong | 80% (68%–92%), 12% wrong | 69% (44%–88%), 19% wrong | 86% (64%–100%), 7% wrong | $0.0047 | | Nemotron 3 Super | 100% (100%–100%), 0% wrong | 77% (64%–90%), 13% wrong | 56% (31%–81%), 31% wrong | 86% (64%–100%), 7% wrong | $0.0054 | | Nemotron 3.5 Super VL | – | 77% (64%–90%), 8% wrong | 75% (50%–94%), 19% wrong | 100% (100%–100%), 0% wrong | $0.0076 | | DeepSeek V4 Flash | 100% (100%–100%), 0% wrong | 70% (55%–82%), 8% wrong | **75%** (50%–94%), 19% wrong | **100%** (100%–100%), 0% wrong | $0.0021 | | Nemotron 3.5 Lightning | 96% (90%–100%), 4% wrong | 65% (50%–80%), 20% wrong | 69% (44%–88%), 25% wrong | 64% (36%–86%), 36% wrong | $0.0028 | | Nemotron 3 Ultra | 100% (100%–100%), 0% wrong | 57% (42%–72%), 15% wrong | 62% (38%–88%), 38% wrong | 0% (0%–0%), 100% wrong | $0.0244 | | gpt-oss 120B | 96% (90%–100%), 4% wrong | 55% (40%–70%), 28% wrong | 56% (31%–81%), 44% wrong | 57% (29%–79%), 14% wrong | $0.0018 | | Qwen3 30B A3B | **98%** (94%–100%), 2% wrong | 50% (35%–65%), 35% wrong | 62% (38%–88%), 31% wrong | 79% (57%–100%), 21% wrong | $0.0009 | | Nemotron 3.5 Lightning (no thinking) | 94% (86%–100%), 6% wrong | 38% (22%–52%), 52% wrong | 56% (31%–81%), 44% wrong | – | $0.0005 | | Nemotron 3 Nano | 96% (90%–100%), 4% wrong | – | – | 86% (64%–100%), 0% wrong | – | Bold: the pick for that set (cheapest model not credibly more than 10 points below the best). Ranges: bootstrap 95% intervals. "Wrong" counts confident wrong answers, not "unknown". Per-question replay: see the Space. ## Run-to-run variance (hard set, two passes) | Model | Run 1 | Run 2 | Questions that flipped | |---|---:|---:|---:| | Reflection Beam | 82% | 79% | 5 of 39 | | Claude Opus 5 | 88% | 90% | 3 of 40 | | Nemotron 3 Super | 77% | 62% | 8 of 39 | | Qwen3 30B A3B | 49% | 41% | 9 of 39 | ## Caveats - Small sets: intervals are wide, read them before the point estimates. - An early bug cached Tavily rate-limit replies as empty searches; affected runs were removed and rerun. See REPRODUCE.md in the repo. - Nemotron 3 Ultra's tool calls came back from Token Factory as raw `` text or under invented tool names when 8 tools were offered (with one tool it called it correctly). This looks like a serving or chat-template issue, not the model's ability. - Prices are Token Factory list prices on 18 October 2026. - Facts with dates ("as of October 2026") can go stale. ## Licence Our questions and run logs: CC BY 4.0. `hard_multihop` items come from FRAMES (Apache 2.0, Google).