Gemma 4 31B (Reasoning) API Provider Benchmarking & Analysis
This analysis is intended to support you in choosing the best API provider of Gemma 4 31B (Reasoning) for your use-case.
Lowest Time per Task
Time per Intelligence Index task (minutes)
Total 10 providers
Lowest Cost per Task
Cost per Intelligence Index task
Total 10 providers
Gemma 4 31B is available through 10 API providers, each offering different performance characteristics and pricing. Below is a comparison of the key metrics across providers.
Pricing
Cost per Intelligence Index Task: Gemma 4 31B (Reasoning)
Pricing: Cache Hit, Input, and Output: Gemma 4 31B (Reasoning)
Output Speed vs. Cost per Task: Gemma 4 31B (Reasoning)
Speed
Average of the single-request and multi-turn agentic workloads measured
Output Speed: Gemma 4 31B (Reasoning)
Latency
Average of the single-request and multi-turn agentic workloads measured
Time to First Answer Token: Gemma 4 31B (Reasoning)
Reliability
Share of requests the endpoint failed, across all the single-request and multi-turn agentic workloads measured
Endpoint Error Rate: Gemma 4 31B (Reasoning)
Caching
Cache Hit Rate: Gemma 4 31B (Reasoning)
Cost per Task vs. Cache Hit Rate: Gemma 4 31B (Reasoning)
Key Comparison Metrics & API Features
 CoreWeave | -- | -- | 7.67 | 0.0% | 262k | Open | ||
 Crusoe | -- | -- | 29.50 | 3.4% | 262k | Open | ||
 DeepInfra | -- | -- | 52.37 | 0.0% | 262k | Open | ||
 DigitalOcean | -- | -- | 34.45 | 0.0% | 262k | Open | ||
 FriendliAI | -- | -- | 9.46 | 0.0% | 256k | Open | ||
 Google | -- | -- | 26.61 | 0.0% | 262k | Open | ||
 Modular | -- | -- | 4.34 | 0.0% | 262k | Open | ||
 Novita | -- | -- | 62.27 | 0.0% | 262k | Open | ||
 Parasail | -- | -- | 22.88 | 4.5% | 262k | Open | ||
 SambaNova | -- | -- | 12.11 | 0.0% | 131k | Open | ||
 SiliconFlow | -- | -- | 14.63 | 2.5% | 262k | Open | ||
Frequently Asked Questions
Common questions about Gemma 4 31B (Reasoning) providers
Gemma 4 31B (Reasoning) is available through 10 API providers: CoreWeave, Modular (NVFP4), Novita, Google (AI Studio), Parasail, DeepInfra, Crusoe, SiliconFlow (FP8), SambaNova, and FriendliAI. Each provider offers different performance characteristics and pricing.
Gemma 4 31B (Reasoning) is currently available through 10 API providers that we benchmark and track.
The providers with the lowest time to first answer token for Gemma 4 31B (Reasoning) are Modular (NVFP4) (4.42s), CoreWeave (7.63s), and FriendliAI (9.93s). Lower latency means faster initial response time.
The most affordable providers for Gemma 4 31B (Reasoning) by blended price are Google (AI Studio) ($0.00 per 1M tokens), Parasail ($0.11 per 1M tokens), and CoreWeave ($0.12 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 Gemma 4 31B (Reasoning) are Google (AI Studio) ($0.00 per 1M input tokens), CoreWeave ($0.10 per 1M input tokens), and Novita ($0.14 per 1M input tokens).
The providers with the lowest output token pricing for Gemma 4 31B (Reasoning) are Google (AI Studio) ($0.00 per 1M output tokens), CoreWeave ($0.34 per 1M output tokens), and Novita ($0.40 per 1M output tokens).
Prices for Gemma 4 31B (Reasoning) range from $0.00 per 1M tokens at Google (AI Studio) to $0.78 per 1M tokens at SiliconFlow (FP8).
All 10 providers of Gemma 4 31B (Reasoning) support JSON mode for structured output.
All 10 providers of Gemma 4 31B (Reasoning) support function calling (tool use).
When choosing a provider for Gemma 4 31B (Reasoning), consider: time per task (how quickly the provider completes an Intelligence Index task), 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 Gemma 4 31B (Reasoning)'s intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview