Best open-weight model for a support agent

Compare with other models

The open-weight models score well on several of the dimensions we test. DeepSeek V4.1 Flash scores 97 on tool use, while GLM 5.3 Flash and Qwen3.8 27B score 95 and 94 on task completion. But the share of conversations with no unsupported claims is still only 48% at best.

Start with DeepSeek. It scores 85 on quality at about $0.013 per conversation. Qwen offers similar quality, but costs almost twice as much. Gemma 4 31B is cheaper and faster than both, at a lower quality score of 77.

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Published benchmark results for selected models
Metric DeepSeek Sep 15, 2026 Alibaba Oct 22, 2026 Zhipu Sep 10, 2026 Google Sep 8, 2026
Overview
Quality score 85 #2 of 17 82 #6 of 17 81 #7 of 17 77 #10 of 17
Median reply 5.1s Served by Phala 5.1s Served by Wafer 6.4s Served by Together 2.5s Best among selected models Served by CoreWeave
Cost per conversation $0.013 $0.024 $0.011 $0.0079 Best among selected models
Quality scores
Tool use 97 Best among selected models 89 96 69
Task completion 89 94 95 Best among selected models 79
Context retention 81 85 Best among selected models 75 79
Grounding 93 Best among selected models 92 90 92
Safety 96 Best among selected models 90 94 90
Hallucinations % of conversations with no unsupported claims detected 48% Best among selected models 33% 24% 48% Best among selected models
Running stats
p95 reply 19.6s 22.1s 34.9s 16.2s Best among selected models
Consistency % of repeat runs ended the same way 85% Best among selected models 79% 82% 82%
Output per turn 450 tokens, median 693 tokens, median 600 tokens, median 88 tokens, median

Reply times cover the model call only. Cost estimates use token usage at list prices.

This whole report is one Voxli workspace: simulated customers, assertion checks, and a frozen, versioned test set that reruns when new models ship.

Test set v3f-2026-09 · edition 2026-09-08