Gemini 3.8 Flash — plus Veo 3.1 video, Lyria 3.5 music, and Gemini Omni
Google DeepMind's Gemini 3.x family spans Gemini 3.8 Flash (latest, promotional pricing until Dec 31 2026), Gemini 3.7 Flash, Gemini 3.6 Flash, Gemini 3.5 Flash, and Gemini 3.1 Pro Preview. The platform has expanded far beyond text: Veo 3.1 for video generation, Lyria 3.5 for music generation, Gemini Omni for video generation, and Gemini Embedding 2 for multimodal embeddings. Gemma 4 open-weight models are free via the API. Check the live table for current per-token rates.
A wide multimodal AI API — text, image, video (Veo 3.1), music (Lyria 3.5), speech, transcription, and robotics under one key, with Gemini 3.8 Flash at promotional pricing until end of 2026.
- Gemini 3.8 Flash: promotional pricing until Dec 31 2026 — check live table for current rates
- Wide multimodal API: text, image, audio, video generation, music, speech, transcription
- Veo 3.1 video generation (720p/1080p/4K)
- Gemma 4 open-weight models free via API
- Free tier via Google AI Studio for prototyping
- Google Search grounding: 5,000 free requests/month on Gemini 3.x
- Promotional pricing expires Jan 1 2027 — prices double
- Complex tiered pricing based on context length (≤200K vs >200K)
- API reliability has historically lagged OpenAI
Google Models
| Model | Modality | Tier | Price | Cached /1M | TTFT | Throughput | Context | Intel. | Caps | |
|---|---|---|---|---|---|---|---|---|---|---|
gemma-4-26b Gemma 4 | Chat | budget | — No current price available | — | 250ms | 200 t/s | 256K | 73 | ||
gemma-4-e2b Gemma 4 | Chat | budget | — No current price available | — | 120ms | 400 t/s | 128K | 58 | ||
gemma-4-e4b Gemma 4 | Chat | budget | — No current price available | — | 140ms | 350 t/s | 128K | 62 | ||
gemma-3-4b Gemma 3 | Chat | budget | — No current price available | — | 130ms | 380 t/s | 128K | 55 | ||
gemma-3-1b Gemma 3 | Chat | budget | — No current price available | — | 80ms | 600 t/s | 32K | 42 | ||
text-embedding-004 Google Embeddings | Embedding | budget | — No current price available | — | 100ms | 0 t/s | 2K | 0 | ||
gemini-embedding-exp-03-07 Gemini Embeddings | Embedding | budget | — No current price available | — | 120ms | 0 t/s | 8K | 0 | ||
imagen-4 Imagen | Image | frontier | $0.04 per image EST Jul 2026 | — | 6.0s | 0 t/s | 4K | 0 | ||
imagen-4-ultra Imagen | Image | frontier | $0.08 per image EST Jul 2026 | — | 9.0s | 0 t/s | 4K | 0 | ||
veo-3 Veo | Video | frontier | $0.35 per second EST Jul 2026 | — | 30.0s | 0 t/s | 4K | 0 | ||
veo-2 Veo | Video | advanced | $0.20 per second EST Jul 2026 | — | 25.0s | 0 t/s | 4K | 0 | ||
gemma-3-12b-it Gemma 3 | Chat | budget | $0.04/ $0.08 in / out per 1M EST Jul 2026 | — | 180ms | 400 t/s | 131K | 52 | ||
gemini-1.5-flash Gemini 1.5 | Chat | budget | $0.07/ $0.30 in / out per 1M EST Jul 2026 | $0.02 | 200ms | 350 t/s | 1.0M | 58 | ||
gemini-2.0-flash-lite Gemini 2.0 | Chat | budget | $0.07/ $0.30 in / out per 1M EST Jul 2026 | — | 180ms | 400 t/s | 1.0M | 50 | ||
gemini-2.0-flash Gemini 2.0 | Chat | budget | $0.10/ $0.40 in / out per 1M EST Jul 2026 | — | 250ms | 280 t/s | 1.0M | 60 | ||
gemma-3-27b-it Gemma 3 | Chat | efficient | $0.10/ $0.20 in / out per 1M EST Jul 2026 | — | 300ms | 220 t/s | 131K | 62 | ||
gemma-4-31b Gemma 4 | Chat | efficient | $0.14/ $0.40 in / out per 1M EST Jul 2026 | — | 280ms | 180 t/s | 256K | 76 | ||
gemini-2.5-flash Gemini 2.5 | Chat | efficient | $0.15/ $0.60 in / out per 1M EST Jul 2026 | $0.04 | 350ms | 220 t/s | 1.0M | 72 | ||
gemini-3.1-flash-lite Gemini 3.1 | Chat | budget | $0.25/ $1.50 in / out per 1M EST Jul 2026 | — | 200ms | 280 t/s | 1.0M | 75 | ||
gemini-3-flash-preview Gemini 3 | Chat | efficient | $0.50/ $3.00 in / out per 1M EST Jul 2026 | — | 300ms | 200 t/s | 1.0M | 82 | ||
gemini-2.5-pro Gemini 2.5 | Chat | frontier | $1.25/ $10.00 in / out per 1M EST Jul 2026 | $0.31 | 900ms | 90 t/s | 1.0M | 87 | ||
gemini-1.5-pro Gemini 1.5 | Chat | advanced | $1.25/ $5.00 in / out per 1M EST Jul 2026 | $0.31 | 800ms | 100 t/s | 2.1M | 74 | ||
gemini-3.5-flash Gemini 3.5 | Chat | advanced | $1.50/ $9.00 in / out per 1M EST Jul 2026 | — | 400ms | 160 t/s | 1.0M | 87 | ||
gemini-3-pro-preview Gemini 3 | Chat | frontier | $2.00/ $12.00 in / out per 1M EST Jul 2026 | — | 700ms | 100 t/s | 1.0M | 91 | ||
gemini-3.1-pro-preview Gemini 3.1 | Chat | frontier | $2.00/ $12.00 in / out per 1M EST Jul 2026 | — | 750ms | 95 t/s | 1.0M | 92 | ||
gemini-4-argon Gemini 4 | Chat | frontier | $2.00/ $10.00 in / out per 1M EST Oct 2026 | — | 900ms | 90 t/s | 1.0M | 94 |
Google — Frequently Asked Questions (FAQs)
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Full comparison tableGoogle LLM pricing overview
Google is a proprietary AI lab that develops and hosts its own large language models. Google DeepMind's Gemini 3.x family spans Gemini 3.8 Flash (latest, promotional pricing until Dec 31 2026), Gemini 3.7 Flash, Gemini 3.6 Flash, Gemini 3.5 Flash, and Gemini 3.1 Pro Preview. The platform has expanded far beyond text: Veo 3.1 for video generation, Lyria 3.5 for music generation, Gemini Omni for video generation, and Gemini Embedding 2 for multimodal embeddings. Gemma 4 open-weight models are free via the API. Check the live table for current per-token rates. Common use cases include Vision, Long-context, Coding, Multimodal. Headquartered in Mountain View, CA, founded 1998. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
Google vs other LLM providers
Google competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. A wide multimodal AI API — text, image, video (Veo 3.1), music (Lyria 3.5), speech, transcription, and robotics under one key, with Gemini 3.8 Flash at promotional pricing until end of 2026. Use the LLM provider comparison tool to see Google token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose Google?
Google stands out because: A wide multimodal AI API — text, image, video (Veo 3.1), music (Lyria 3.5), speech, transcription, and robotics under one key, with Gemini 3.8 Flash at promotional pricing until end of 2026.. The API currently offers 26 models, spanning 7 frontier, 3 advanced, 4 efficient, 12 budget tiers. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding Google token pricing
Google charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. The cheapest {meta.name} input rate is currently $0.04/1M tokens. Prices shown are sourced from Google's public pricing page and updated every 15 minutes. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
Google context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. Google's largest context window is 2.1M tokens. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when Google makes sense
Managed inference APIs like Google eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at Google API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical Google token price data is available in the LLM price history charts.
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