TIR-Bench
A tool-calling and multimodal interaction benchmark for testing visual instruction following and execution reliability.
Qwen3.6 Plus from Alibaba Cloud / Qwen Team currently leads the TIR-Bench leaderboard with a score of 0.616 across 4 evaluated AI models.
What TIR-Bench measures
TIR-Bench is a multimodal benchmark that evaluates large language models on multimodal, reasoning, agents, and tool calling tasks. LLM Stats tracks 4 models on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.6, with the leader reaching 0.6.
Compare leaders on the best AI for multimodal, best AI for reasoning, best AI for agents and best AI for tool calling leaderboards.
Qwen3.6 Plus leads with 61.6%, followed by Qwen3.5-27B at 59.8% and Qwen3.5-35B-A3B at 55.5%.
Progress Over Time
Interactive timeline showing model performance evolution on TIR-Bench
TIR-Bench Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | — | 1.0M | $0.50 / $3.00 | ||
| 2 | Alibaba Cloud / Qwen Team | 27B | 262K | $0.30 / $2.40 | ||
| 3 | Alibaba Cloud / Qwen Team | 35B | 262K | $0.25 / $2.00 | ||
| 4 | Alibaba Cloud / Qwen Team | 122B | 262K | $0.40 / $3.20 |
FAQ
Common questions about TIR-Bench.
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