Skip to content
Tier B — Production
Runs in:FranceMade in:China

Archived

This model has been discontinued by the provider. Historical data is preserved.

No longer available since September 20, 2026.

OVH AI Endpoints (GRA)

Qwen3-32B

Tier B — Production

Tokonomix Editorial Team·Reviewed by Mes Kalkan··
Section 01

Pricing

What you pay per million tokens when you use this model on Tokonomix, plus an estimate for a typical conversation.

💰
API rates — Qwen3-32B
$0.2100 per 1M input tokens
$0.6000 per 1M output tokens
≈ $0.0002 per typical conversation (800 tokens)
Input vs output price (per 1M tokens)
per 1M input tokens$0.2100
per 1M output tokens$0.6000
Section 02

Capabilities

ownedBy: Qwen
Section 03

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.

Section 04

Tokonomix benchmark verdicts

⚖️
Endorsed by 2 judges
Independent LLM judges evaluated this model on our weekly intelligence tests
cohere/command-a95/100 · 1 runs
1 correct0 partial0 wrong100% accuracy
claude-sonnet-4-576/100 · 82 runs
51 correct16 partial15 wrong62% accuracy
● 2026-09-13

Qwen3-32B drops to 56.8 quality, latency improves 17% to 18.0s

Qwen3-32B shows a mixed performance shift in this benchmark window, with overall quality declining slightly from 58.0 to 56.8 while latency improved meaningfully from 21.7s to 18.0s. The 17% latency improvement brings response times closer to acceptable levels, though they remain notably high for a 32B parameter model. Category performance reveals dramatic swings: reasoning capability jumped impressively to 89 from a previous coding score of 52, and coding maintained strong performance at 72. However, factual accuracy collapsed to just 10, a concerning regression that suggests significant reliability issues with knowledge-based queries. The previous window's multilingual strength at 91 and creative capabilities are not represented in current testing categories, making direct comparison incomplete. This benchmarking period captures only 5 test runs, matching the previous window's sample size. Users should exercise caution with factual queries given the severe accuracy drop, while those prioritizing reasoning tasks may find improved utility. The latency gains are welcome but the model still requires substantial patience per request. Overall trajectory remains uncertain given the quality decline despite operational improvements.

Quality

56.8

Latency p50

17,953 ms

Test runs

5

✓ Latency improved 17%✗ Quality dropped to 56.8✗ Factual accuracy collapsed to 10✓ Reasoning strong at 89
Last automated test
Sep 20, 2026 · 05:11 UTC · Benchmark
P50 latency
—
P95 latency
—
Errors
1 / 6 runs
Last reviewed by Tokonomix Team·September 20, 2026