Speed analysis
Latency measured across all benchmark runs. P50 (median) and P95 (95th percentile) give a realistic picture of response speed under normal and peak load.
Quality scores
How this model compares to the rest of the field on each prompt category, from a pairwise fit over the same prompts. The raw judge score sits underneath each number.
Win rate per category: how often this model beats a field-average model on a prompt from that category. 50% is average, not a failing grade. It is not a percentage of correct answers.
Pricing
What you pay per million tokens when you use this model on Tokonomix, plus an estimate for a typical conversation.
Tokens per second
Throughput in tokens per second, derived from measured P50 latency. Higher is better; fluctuations track provider-side load.
Estimated from P50 latency × 200 output tokens — the absolute number depends on this assumption; the trend is what matters.
Capabilities
Availability
Availability
No measurements yet
We haven't recorded enough API calls to show availability stats for this model. Data appears once the model starts receiving live traffic.
Tokonomix benchmark verdicts
Quality falls 9.5 points to 75.2 with near-doubled latency
Qwen3-Coder-30B-A3B-Instruct demonstrates significant performance degradation in this benchmark window. Overall quality dropped from 84.7 to 75.2, representing a 9.5 point decline that follows a previous 6.5 point decrease. This marks a concerning downward trend across consecutive windows. Latency deteriorated substantially, with p50 response times increasing 93% from 2009ms to 3886ms, nearly doubling the wait time for users. Category performance shows mixed results with sharp variations. Reasoning achieved a perfect 100 score, indicating strong logical capabilities. However, coding performance plummeted from 94 to 69, a 25 point drop that undermines the model's core positioning as a coding specialist. Factual accuracy scored 57, though this represents a new category without direct comparison. The previous window's multilingual and creative categories were not tested in the current period. The combination of declining quality metrics and significantly increased latency suggests potential infrastructure or model configuration issues. Users should expect notably slower responses and reduced coding performance compared to the previous benchmark period. The perfect reasoning score provides limited consolation given the substantial regression in the model's primary coding capabilities.
Quality
75.2
Latency p50
3,886 ms
Test runs
5
Qwen3-Coder-30B-A3B-Instruct
by OVH AI Endpoints (GRA)
- Context window
- — tokens
- Input price
- $0.1900 / 1M
- Output price
- $0.6800 / 1M
- Tier
- Tier B — Production
- Modality
- Text
- API type
- REST · streaming
- Benchmark runs
- 522
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