Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.
Modalities
In / Out Price
$0.09 / $0.34per 1M
Context
262K
Released
Apr 2, 2026
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), Floor (cheapest), or Exacto (highest tool-calling accuracy).
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.
| Source | Benchmark | Score |
|---|---|---|
| Artificial Analysis | Gemma 4 31B (Non-reasoning) Coding Index | 33.2 |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) GPQA Diamond | 76.3% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) HLE | 11.8% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) IFBench | 53.5% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) τ²-Bench Telecom | 65.5% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) AA-LCR | 46.7% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) GDPval-AA | 9.6% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) CritPt | 0.0% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) Terminal-Bench Hard | 30.3% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) AA-Omniscience Accuracy | 16.6% |
| Artificial Analysis | Gemma 4 31B (Non-reasoning) AA-Omniscience Non-Hallucination Rate | 18.1% |
| Artificial Analysis | Gemma 4 31B (Reasoning) Intelligence Index | 15.4 |
| Artificial Analysis | Gemma 4 31B (Reasoning) Coding Index | 43.4 |
| Artificial Analysis | Gemma 4 31B (Reasoning) Agentic Index | 6.7 |
| Artificial Analysis | Gemma 4 31B (Reasoning) GPQA Diamond | 85.7% |
| Artificial Analysis | Gemma 4 31B (Reasoning) HLE | 23.6% |
| Artificial Analysis | Gemma 4 31B (Reasoning) IFBench | 75.6% |
| Artificial Analysis | Gemma 4 31B (Reasoning) τ²-Bench Telecom | 59.9% |
| Artificial Analysis | Gemma 4 31B (Reasoning) AA-LCR | 69.7% |
| Artificial Analysis | Gemma 4 31B (Reasoning) GDPval-AA | 12.8% |
| Artificial Analysis | Gemma 4 31B (Reasoning) CritPt | 1.4% |
| Artificial Analysis | Gemma 4 31B (Reasoning) SciCode | 45.5% |
| Artificial Analysis | Gemma 4 31B (Reasoning) Terminal-Bench Hard | 36.4% |
| Artificial Analysis | Gemma 4 31B (Reasoning) AA-Omniscience Accuracy | 20.0% |
| Artificial Analysis | Gemma 4 31B (Reasoning) AA-Omniscience Non-Hallucination Rate | 15.0% |
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Token volume and request traffic to this model over time.
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
| $0.09 | $0.34 | $0.05 | 0.87s | 30 tps | ||
| $0.10 | $0.34 | $0.10 | 1.13s | 26 tps | ||
| $0.12 | $0.36 | $0.09 | 0.73s | 28 tps | ||
| $0.12 | $0.37 | $0.012 | 3.21s | 20 tps | ||
| $0.13 | $0.38 | -- | 1.00s | 21 tps | ||
| $0.14 | $0.40 | -- | 0.29s | 145 tps | ||
| $0.14 | $0.40 | -- | 0.71s | 16 tps | ||
| $0.15 | $0.40 | $0.06 | 1.70s | 19 tps | ||
| $0.27 | $0.76 | -- | 2.09s | 84 tps | ||
| $0.38 | $1.15 | -- | 1.50s | 61 tps | ||
| $0.39 | $0.97 | -- | -- | -- | ||
| $0.75 | $1.00 | $0.75 | 0.15s | 107 tps | ||
| $0.14 | $0.40 | $0.14 | 1.07s | 14 tps | ||
| $0.75 | $1.00 | $0.25 | 2.64s | 21 tps |
Throughput
145tok/s
P50, best across providers
Latency
0.15s
P50, best provider
100.00%
99.80%
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.
Gemma 4 31B costs $0.09/M input tokens and $0.34/M output tokens, with separate rates for Cache Read at $0.05/M tokens.
Gemma 4 31B has a 262,144 token context window. It supports up to 16,384 completion tokens.
Yes. Gemma 4 31B accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Gemma 4 31B accepts images, text, and video as input and returns text.
Gemma 4 31B is served by 12 providers on OpenRouter: DeepInfra Ultra, CoreWeave, Venice, Chutes, Crusoe, Friendli, NovitaAI, Parasail and 4 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
Gemma 4 31B was released on April 2, 2026.