This model is deprecated. We only continue performance benchmarking for the default 10k input token workload. Results for other workloads are historical and no longer updated.
Alibaba has launched a newer release, Qwen3 30B A3B 2507 (Reasoning). We suggest considering it instead.
Qwen3 32B (Reasoning) API Provider Benchmarking & Analysis
This analysis is intended to support you in choosing the best API provider of Qwen3 32B (Reasoning) for your use-case.
Fastest
DeepInfra (FP8)Output speed
Total 2 providers
Lowest Latency
DeepInfra (FP8)Time to first answer token
Total 2 providers
Lowest Price
DeepInfra (FP8)
SambaNovaBlended price (per 1M tokens)
Total 2 providers
Qwen3 32B is available through 2 API providers, each offering different performance characteristics and pricing. Below is a comparison of the key metrics across providers.
- For output speed, the top providers are DeepInfra (FP8) (27.2 t/s).
- For latency, DeepInfra (FP8) (75.15s) offer the lowest time to first answer token.
- For pricing, DeepInfra (FP8) (0.10) and SambaNova (0.44) offer the lowest blended prices per 1M tokens.
- DeepInfra (FP8) stands out as the overall leader, ranking first across all three categories: speed, latency, and pricing.
Pricing
Pricing: Cache Hit, Input, and Output
Cost per Intelligence Index Task
Output Speed vs. Price
Speed
Measured by Output Speed (tokens per second)
Output Speed: Qwen3 32B (Reasoning)
Time per Intelligence Index Task
Cost per Task vs. Time per Task
Latency
Measured by Time (seconds) to First Token
Time to First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Key Comparison Metrics & API Features
Frequently Asked Questions
Common questions about Qwen3 32B (Reasoning) providers
Qwen3 32B (Reasoning) is available through 2 API providers: DeepInfra (FP8) and SambaNova. Each provider offers different performance characteristics and pricing.
Qwen3 32B (Reasoning) is currently available through 2 API providers that we benchmark and track.
The fastest provider for Qwen3 32B (Reasoning) by output speed is DeepInfra (FP8) (27.2 t/s). Output speed measures how quickly tokens are generated after the model starts responding.
The provider with the lowest time to first answer token for Qwen3 32B (Reasoning) is DeepInfra (FP8) (75.15s). Lower latency means faster initial response time.
The most affordable providers for Qwen3 32B (Reasoning) by blended price are DeepInfra (FP8) ($0.10 per 1M tokens) and SambaNova ($0.44 per 1M tokens). Blended price uses a 7:2:1 cache hit/input/output token ratio.
The providers with the lowest input token pricing for Qwen3 32B (Reasoning) are DeepInfra (FP8) ($0.08 per 1M input tokens) and SambaNova ($0.40 per 1M input tokens).
The providers with the lowest output token pricing for Qwen3 32B (Reasoning) are DeepInfra (FP8) ($0.28 per 1M output tokens) and SambaNova ($0.80 per 1M output tokens).
Prices for Qwen3 32B (Reasoning) vary up to 4.4x across providers. The most affordable is DeepInfra (FP8) at $0.10 per 1M tokens, while SambaNova charges $0.44 per 1M tokens.
All 2 providers of Qwen3 32B (Reasoning) support JSON mode for structured output.
All 2 providers of Qwen3 32B (Reasoning) support function calling (tool use).
DeepInfra (FP8) leads across all key metrics for Qwen3 32B (Reasoning), offering the fastest speed, lowest latency, and most competitive pricing.
When choosing a provider for Qwen3 32B (Reasoning), consider: output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and API features like JSON mode or function calling.
Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.
For information about Qwen3 32B (Reasoning)'s intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview