Gemini 3 FlashAPI Pricing

Gemini API Pricing: Google's 2026 Model Costs Breakdown

Google's Gemini 3 family is aggressively priced, especially the Flash tier which undercuts most competitors. Here's what every tier costs and when each one makes sense.

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You only pay credits per request. No monthly subscription. Paid credits never expire.

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Why teams start here first
No monthly subscription
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Start with trial credits, then buy only what you consume.
Failover safety
Production-ready routing
Auto fallback across providers when latency, quality, or reliability changes.
Data control
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BYOK and zero-retention mode keep training and storage scope explicit.
Single API experience
One key, multi-provider access
Use Chat/Compare/Blend/Judge/Failover from one dashboard.
Google API pricing (reference)

Kept as reference for model evaluation. LLMWise pricing shown below is request-based credits.

TierInput / 1M tokensOutput / 1M tokensContextNote
Gemini 3 Flash$0.15$0.601M tokensUltra-low-cost model with 1M context window. Excellent for summarization, translation, and high-volume classification. Supports vision and grounding.
Gemini 3 Pro$2.00$8.002M tokensMid-tier model with the largest context window available. Strong at multi-document analysis, research tasks, and complex reasoning.
Gemini 3 Ultra$6.00$24.002M tokensGoogle's most capable model. Top-tier coding, math, and multimodal understanding. Competitive with GPT-5.2 and Opus 4.6.
User-facing pricing is request-based, not per token
Evidence snapshot

Gemini 3 Flash pricing analysis

Current Gemini 3 Flash billing context: compare providers, then run the same workload on LLMWise for request-based credits.

LLMWise usage
Chat 1, Compare 3, Blend 4, Judge 5, Failover 1
fixed credits per request
Pricing tiers
3
provider options for this model family
LLMWise scenario cost
Usage-equivalent spend on LLMWise pay-per-use credits (paid credits do not expire)
10,000 chat messages per month (avg 800 input + 400 output tokens each)
Savings result
Gemini Flash is so cheap that direct API is cost-effective — but LLMWise adds failover, analytics, and multi-model access for a small premium
based on workload mix and routing auto-mode
Usage starts-to-finish

Example: Product support workload

If your team sends 20 support messages a day in Chat mode, you typically use around 600 credits each month (1 credit/request).

Workflow
20 req/day
Chat mode / 1 credit each
Monthly estimate
600 credits
before optional auto-topup
What you get
Predictable
same behavior, single model switch
Try this scenario in your dashboard

Why people use LLMWise

API key setup
One LLMWise API key — no Google Cloud account needed to access Gemini
See Google comparison
Google Cloud project required, enable Vertex AI or use AI Studio key
Billing model
Simple pay-per-use credits with one balance across all supported models
See Google comparison
Google Cloud billing with monthly invoicing, complex pricing tiers
Failover
Automatic failover to GPT-5.2 or Claude if Gemini returns errors
See Google comparison
No built-in failover — must implement your own retry logic
Model switching
Same endpoint and key for Gemini, GPT-5.2, Claude, and all other models
See Google comparison
Different SDKs for Vertex AI vs AI Studio, separate auth flows
Rate limits
Pooled multi-provider capacity — exceed single-provider limits seamlessly
See Google comparison
Generous free tier (15 RPM), paid tier up to 2,000 RPM
Free tier
40 free trial credits on signup — test Gemini against every other model
See Google comparison
Free tier available: 15 RPM for Flash, limited daily quota for Pro
Cost example

10,000 chat messages per month (avg 800 input + 400 output tokens each)

LLMWise total
Usage-equivalent spend on LLMWise pay-per-use credits (paid credits do not expire)
You save
Gemini Flash is so cheap that direct API is cost-effective — but LLMWise adds failover, analytics, and multi-model access for a small premium
Optional: reference direct API cost

$3.60/mo with Gemini 3 Flash ($1.20 input + $2.40 output)

Gemini 3 Flash is the cheapest mainstream LLM API in 2026, making it ideal for high-volume, cost-sensitive workloads. Direct API access is extremely affordable, but you give up failover and multi-model flexibility. LLMWise makes sense when you want Gemini as your primary model with automatic fallback to Claude or GPT-5.2 during outages, or when you need to compare Gemini's output against other models.

Common questions

How much does Gemini 3 Flash cost per token?
Gemini 3 Flash costs $0.15 per million input tokens and $0.60 per million output tokens, making it one of the cheapest commercial LLM APIs available in 2026. For reference, processing 1 million tokens of input costs about the same as a cup of coffee.
Is Gemini cheaper than GPT-5 and Claude?
Yes, significantly. Gemini 3 Flash ($0.15/$0.60 per 1M tokens) is roughly 20x cheaper than GPT-5.2 ($3.00/$12.00) and 17x cheaper than Claude Sonnet 4.5 ($2.50/$10.00) on input tokens. Even Gemini 3 Pro ($2.00/$8.00) undercuts both flagship competitors.
Does Gemini have a free tier?
Yes. Google offers a free tier for Gemini through AI Studio with 15 requests per minute for Flash and limited daily quotas for Pro. This is generous for prototyping but insufficient for production workloads. LLMWise also offers 40 free trial credits at signup.
What is the Gemini 3 context window size?
Gemini 3 Flash supports up to 1 million tokens of context, and Gemini 3 Pro/Ultra support up to 2 million tokens. These are the largest context windows available from any major LLM provider, making Gemini especially suited for analyzing long documents, codebases, and multi-turn conversations.

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You only pay credits per request. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

Chat, Compare, Blend, Judge, MeshPolicy routing + replay labFailover without extra subscriptions
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Related pages
DeepSeek V3 PricingLlama 4 Maverick PricingGrok 3 PricingCheapest LLM API: Best Value AI Models for DevelopersGPT-5.2 PricingClaude Sonnet 4.5 Pricing