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Gemma 4 31B (free)
- Instruction Following
Gemma 4 31B (free) is a large language model from Google’s Gemma 4 family, offered in a 31-billion-parameter configuration with free access in some platforms. It is positioned as a capable general-purpose model for text generation and understanding.
About the model
What is Gemma 4 31B (free)?
Gemma 4 31B (free) is a 31-billion-parameter variant of Google’s Gemma 4 large language model made available at no cost on certain services. It is mainly used for tasks like conversational agents, content drafting, and general-purpose question answering. It is also suited to code assistance, basic analysis of text, and other common LLM workflows where a strong but not maximal-size model is appropriate. It belongs to Google’s Gemma model family, which is the successor line to earlier Gemma releases.
Model capabilities
5 Core Capabilities
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Conversational Chat
Handles multi-turn conversations, answers questions, and maintains context to provide helpful, coherent replies across a wide range of topics.
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Code Assistance
Generates and explains code snippets, helps debug issues, and supports common programming languages for educational and practical tasks.
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Multilingual Translation
Translates between multiple languages, preserving meaning and tone for everyday text, technical explanations, and simple documents.
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Vision Understanding
Analyzes user-provided images, identifying objects, text, and overall context to support image-based queries and explanations.
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Image Text Extraction
Reads and extracts textual content from images, enabling users to convert visual documents, screenshots, or photos into editable text.
Use cases
6 Most Valuable Use Cases
- Customer Support Chatbot
- Financial Document Summaries
- Legal Case Research Assistant
- Litigation Docket Monitoring
- Marketing Copy Generation
- Code Assistance and Review
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and highest performance access to Gemma-class 30B models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 120ms | 120 tps | 99.99% | $0.05 | $0.10 | 256K |
| Google AI Studio | Global | ~350ms | ~40 tps | 99.9% | $0.00 | $0.00 | 128K |
| Vertex AI (Google Cloud) | US East | ~380ms | ~35 tps | 99.9% | ~$0.40 | ~$0.80 | 128K |
| Anthropic | US East | ~320ms | ~50 tps | 99.9% | ~$3.00 | ~$15.00 | 200K |
| OpenRouter | Global | ~420ms | ~30 tps | 99.5% | ~$0.35 | ~$0.70 | 128K |
Performance benchmarks
Technical Specifications
| Metric | Gemma 4 31B (free) | GPT‑4.1 mini | Claude 3.5 Haiku |
|---|---|---|---|
| Avg Latency | ~250ms | ~220ms | ~260ms |
| Context Window | 128K | 128K | 200K |
| Input Price ($/1M) | $0.00 | $0.15 | $0.25 |
| Output Price ($/1M) | $0.00 | $0.60 | $1.25 |
| Max Output Tokens | 4K | 4K | 4K |
| Throughput | ~60 tps | ~80 tps | ~70 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
- 62B
- Prompt tokens processed (last 30 days)
- 19B
- Completion tokens generated (last 30 days)
- 3.4M
- API requests served (last 30 days)
- 410K
- Unique users (last 30 days)
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Intelligent Model Routing
Dynamically route each request to the optimal model across providers based on latency, cost, and quality—without changing your integration or redeploying code.
One endpoint, any model -
Cost-Aware Controls
Set hard budgets, price caps, and model tiers so teams can experiment freely while your total LLM spend stays predictable and automatically optimized.
Ship fast, spend less -
Automatic Failover Logic
Define provider and model fallbacks once, then let LLM.API transparently retry, degrade gracefully, and keep responses flowing when vendors hit rate limits or downtime.
Resilient by default -
End-to-End Observability
Get unified logs, traces, and metrics for every request across providers so you can debug issues, compare models, and tune prompts from a single dashboard.
See every token -
Task-Level Abstractions
Describe tasks like chat, extraction, search, or tools once and let LLM.API pick and orchestrate the right models, prompts, and parameters behind the scenes.
Code to tasks, not models -
High-Throughput Batching
Send thousands of requests in a single batch call with concurrency controls and retries, cutting latency and cost for bulk workloads and offline pipelines.
Scale jobs, not code
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a free, reasonably capable general-purpose LLM for prototypes and internal tools.
- You need to handle moderate workloads where occasional latency spikes or throttling are acceptable.
- Your use case involves summarizing short to medium-length documents, emails, or reports.
- Your use case involves basic code explanation, refactoring, or generating simple utility scripts.
- Your use case involves drafting marketing copy, blog outlines, or social media text content.
- You need a backup or fallback model when paid frontier models hit quota limits.
- Your use case involves chat-style assistants that answer common questions with moderate complexity.
Avoid if...
- You need state-of-the-art reasoning performance on complex multi-step or multi-document problems.
- Your workload requires highly reliable enterprise SLAs, priority support, and uptime guarantees.
- You need the strongest safety, red-teaming, and alignment layers for sensitive deployments.
- Your workload requires handling extremely long contexts, such as full books or codebases.
- You need top-tier performance on advanced coding tasks, agents, or autonomous tool use.
- Your workload requires low, predictable latency for real-time interactive or streaming applications.
- You need fine-grained control over model behavior via advanced system prompts or tools.
FAQ
Frequently Asked Questions
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What is Gemma 4 31B (free)?
Gemma 4 31B (free) is a 31-billion-parameter Google language model accessible via LLM.API with no per-token charges for usage.
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What is Gemma 4 31B (free) best suited for?
Gemma 4 31B (free) is best for general-purpose coding assistance, natural language reasoning, and chat-style applications where cost-free experimentation is important.
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What is the context window of Gemma 4 31B (free)?
Gemma 4 31B (free) supports a 8K token context window for combined input and output tokens.
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What modalities does Gemma 4 31B (free) support?
Gemma 4 31B (free) is a text-only model that accepts text prompts and returns text completions.
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How is Gemma 4 31B (free) priced on LLM.API?
Gemma 4 31B (free) is available with zero metered token costs, subject to LLM.API’s global rate limits and fair-use policies.
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What latency should I expect from Gemma 4 31B (free)?
Gemma 4 31B (free) typically has higher latency than smaller models, especially under heavy shared usage, but remains suitable for interactive applications.
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How do I call Gemma 4 31B (free) through LLM.API?
Specify the model name "gemma-4-31b-free" in your LLM.API completion or chat endpoint request, using the same authentication as other models.
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How does Gemma 4 31B (free) compare to smaller Gemma variants?
Compared to smaller Gemma models, Gemma 4 31B (free) generally offers stronger reasoning and coding performance at the cost of increased latency and resource use.
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Does Gemma 4 31B (free) support tools or function calling via LLM.API?
Gemma 4 31B (free) can be used with LLM.API’s tool or function-calling abstractions when supported at the API layer, despite being a base text model.
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What are the main limitations of Gemma 4 31B (free)?
Gemma 4 31B (free) may hallucinate facts, lacks real-time knowledge, is text-only, and can be slower than smaller or paid-optimized alternatives.