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All model benchmarks

Tool calls, BFCL

BFCL v4 slice, one greedy pass

Single requests from the Berkeley Function Calling Leaderboard (BFCL v4), a public tool-calling test: one call, picking between several tools, several calls at once, and requests no tool fits. A case counts only when the calls match an accepted answer exactly. One pass per case at temperature 0, through the Tryll ToolCall node, so the numbers are not the same as the public BFCL leaderboard.

Every model on this page was measured on NVIDIA GeForce RTX 4080 · Vulkan.

Tool calls, BFCL

Tool calls, BFCL Tool calls, BFCL

Measured models

Model Right Interval Rank range Cases Most common mistake Family
Bonsai 8B (Q2_0 2-bit) 85.0% 80.7% to 89.0% #1–5 of 12 255 of 300 wrong argument value (33) Bonsai
Ministral 3 8B Instruct (Q4_K_M) 85.0% 80.7% to 89.0% #1–5 of 12 255 of 300 wrong argument value (32) Ministral
Bonsai 8B (Q1_0 1-bit) 84.7% 80.3% to 88.7% #1–6 of 12 254 of 300 wrong argument value (33) Bonsai
Ministral 3 3B Instruct (Q4_K_M) 84.0% 79.7% to 88.0% #1–7 of 12 252 of 300 wrong argument value (34) Ministral
Qwen 3.5 4B (Q4_K_M) 84.0% 79.3% to 88.3% #1–7 of 12 252 of 300 wrong argument value (33) Qwen
Gemma 4 E2B Instruct QAT (UD-Q4_K_XL) 81.3% 76.7% to 86.0% #3–8 of 12 244 of 300 wrong argument value (30) Gemma
Gemma 4 E4B Instruct (Q4_K_M) 80.7% 76.0% to 85.0% #4–8 of 12 242 of 300 wrong argument value (35) Gemma
Ling 3.0 Tiny (Q4_K_M) 79.3% 74.7% to 84.0% #6–8 of 12 238 of 300 wrong argument value (37) Ling
Granite 4.2 8B Instruct (Q4_K_M) 68.3% 63.0% to 73.3% #9 of 12 205 of 300 missed a call (57) Granite
Granite 4.2 3B Instruct (Q4_K_M) 61.3% 56.0% to 67.0% #10 of 12 184 of 300 missed a call (88) Granite
Llama 3.1 8B Instruct (Q4_K_M) 45.7% 39.7% to 51.3% #11 of 12 137 of 300 missed a call (57) Llama
Llama 3.2 3B Instruct (Q4_K_M) 26.0% 21.0% to 31.0% #12 of 12 78 of 300 right value, wrong type (100) Llama

Model cards

No tool support: SmolLM2 1.7B Instruct (Q4_K_M).