A function-calling benchmark for tool selection, schema adherence, and argument correctness.
BenchLM mirrors the published score view for BFCL v4. Qwen3.7 Max leads the public snapshot at 75.0% , followed by LFM2.5-8B-A1B (49.7%) and ZAYA1-8B (39.2%). BenchLM does not use these results to rank models overall.
Qwen3.7 Max
Alibaba
LFM2.5-8B-A1B
LiquidAI
ZAYA1-8B
Zyphra
The published BFCL v4 snapshot is tightly clustered at the top: Qwen3.7 Max sits at 75.0%, while the third row is only 35.8 points behind. The broader top-10 spread is 53.9 points, so the benchmark still separates strong models even when the leaders cluster.
5 models have been evaluated on BFCL v4. The benchmark falls in the Agentic category. This category carries a 22% weight in BenchLM.ai's overall scoring system. BFCL v4 is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Function-calling tasks
Format
Tool invocation and schema evaluation
Difficulty
Advanced tool use
BenchLM stores BFCL v4 as a display-only function-calling reference outside the current weighted core schema.
Version
BFCL v4 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
A function-calling benchmark for tool selection, schema adherence, and argument correctness.
Qwen3.7 Max by Alibaba currently leads with a score of 75.0% on BFCL v4.
5 AI models have been evaluated on BFCL v4 on BenchLM.
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