# Fixing Tool-Call Accuracy in vLLM

> vLLM 0.31 improves tool call accuracy for Kimi K2.6 and DeepSeek models.
- Title: Fixing Tool-Call Accuracy in vLLM · Ubicloud | Shortify
- Summary: vLLM 0.31 improves tool call accuracy for Kimi K2.6 and DeepSeek models. vLLM 0.31 enables 100% tool call schema accuracy for Kimi K2.6 and DeepSeek models…
- Keywords: vllm, kimi, deepseek, constrained decoding, tool call accuracy, schema adherence, llm inference, technology, startups, Fixing, Tool-Call, Accuracy
- Source: Ubicloud — https://ubicloud.com/blog/fixing-tool-call-accuracy-in-vllm
- Read time: 1 min
- Topics: vllm, kimi, deepseek, constrained decoding, tool call accuracy, schema adherence, llm inference, technology, startups
## Tool Call Accuracy Problem
When serving Kimi K2.6 with vLLM 0.28, tool calls failed 8% of the time.
## Tool Call Schema
The tool call schema defines required parameters and valid formats for external tools.
## vLLM 0.28 Limitation
vLLM 0.28 had 92% tool call schema accuracy for Kimi K2.6 and DeepSeek models.
## Constrained Decoding
Constrained decoding ensures tool calls follow the schema by restricting valid token generation.
## vLLM 0.31 Fix
vLLM 0.31 adds constrained decoding to guarantee 100% schema accuracy for tool calls.
## K2VV Benchmark
The K2VV ToolCall benchmark measures tool call accuracy and schema adherence for LLMs.
## Schema Accuracy
Schema accuracy quantifies how many tool calls follow the defined schema rules.
## vLLM Implementation
vLLM uses XGrammar to implement constrained decoding for tool call validation.
## vLLM 0.25 Issue
vLLM 0.25 had problems with constrained decoding causing tool call accuracy to drop.
## Three Problem Types
vLLM faced three types of issues with constrained decoding: model issues, grammar translation bugs, and feature interactions.
## vLLM 0.31 Solution
vLLM 0.31 enables 100% schema accuracy for Kimi K2.6 and DeepSeek models through constrained decoding.
## vLLM 0.31 Deployment
Ubicloud deployed vLLM 0.31 to improve tool call accuracy for Kimi K2.6 and DeepSeek models.
## vLLM 0.31 Impact
vLLM 0.31 improved tool call accuracy from 92% to 100% for Kimi K2.6 and DeepSeek models.
## vLLM 0.31 Benefits
vLLM 0.31 adds negligible performance overhead while ensuring 100% schema accuracy.
## vLLM 0.31 Next Steps
Ubicloud will share more tool call accuracy improvements for vLLM in future posts.
## Key takeaway

vLLM 0.31 enables 100% tool call schema accuracy for Kimi K2.6 and DeepSeek models by using constrained decoding.