Pricing Comparison: Google Gemini vs DeepSeek pricing - a comparison for AI product builders

Gemini and DeepSeek compete for the price-sensitive end of AI token pricing. DeepSeek wins on price, about 11x cheaper at the flagship level on the workload below. The more interesting difference is direction: Gemini's budget tier has been repricing upward while DeepSeek keeps cutting.

Google vs DeepSeek at a glance

Takeaway: DeepSeek is 11x cheaper at the flagship level. At the small-model end, Flash-Lite and V4 Flash are close on the rate card, and DeepSeek's automatic caching decides it for repetitive workloads.

Model overview

Google's flagship is Gemini 3.1 Pro, in preview at $2 / $12 for prompts up to 200k. Gemini 3.5 Flash, launched May 19, 2026, is the newest speed tier at $1.50 / $9. Gemini 3.1 Flash-Lite at $0.125 / $0.75 is the value pick, and Gemini 2.5 Pro remains on the card as a legacy model being displaced.

DeepSeek runs the shortest rate card in the market: two models. deepseek-v4-pro is the flagship at $0.435 / $0.87 and deepseek-v4-flash is the value pick at $0.14 / $0.28, both with 1M context and automatic caching that drops cache-hit input to fractions of a cent. The deepseek-chat and deepseek-reasoner aliases retire July 24, 2026. The consumer app is free.

Key features

Pricing snapshot

Prices verified July 13, 2026. Providers reprice often, see the update timeline below.

Google API pricing

Per 1M tokens, paid tier, prompts up to 200k where tiered.

Batch: 50% off. Grounded search: $14 per 1k queries after 5,000 free per month. A free tier exists for most Flash models.

DeepSeek API pricing

Per 1M tokens.

The deepseek-chat and deepseek-reasoner aliases retire July 24, 2026. The consumer app is free.

Chat plans

What this costs at a real workload

The standardized scenario: 1,000 requests per day at roughly 1,000 input and 1,000 output tokens each, which works out to about 30M input and 30M output tokens per month. Monthly cost = 30 x input rate + 30 x output rate.

Tokenizer caveat for the Claude rows: Fable 5, Sonnet 5, and Opus 4.7+ use a new tokenizer that produces roughly 30% more tokens for the same text. Comparing per-token rates across providers understates Anthropic's effective cost per request by about that margin. Rate cards don't tell you what the invoice will say. The tokenizer does.

Gemini 3.1 Pro at $420 per month against DeepSeek V4 Pro at $39.15 is the flagship story. At the value end it tightens: Gemini 3.1 Flash-Lite works out to roughly $26 on this math against V4 Flash's $12.60, the closest any Western provider gets to DeepSeek's floor.

The spread across all six providers is 143x between the most and least expensive model for the same workload. The full 15-row table is on the AI Pricing Index. For how per-token rates turn into unit economics, see token economics.

Timeline of past updates

Google

• May 2026 (I/O): AI Ultra restructured, $99.99 5x tier added, 20x tier cut from $249.99 to $199.99

• May 19, 2026: Gemini 3.5 Flash at $1.50 / $9. 3x over Gemini 3 Flash

• February 19, 2026: Gemini 3.1 Pro preview at $2 / $12, 3.1 Flash-Lite at $0.125 / $0.75

• December 17, 2025: Gemini 3 Flash preview at $0.50 / $3, up 67% from 2.5 Flash

• November 18, 2025: Gemini 3 Pro preview at $2 / $12, up from 2.5 Pro's $1.25 / $10

• June 2025: Gemini 2.5 Flash GA at $0.30 / $2.50

Trajectory: The Flash tier is 5x more expensive than 13 months ago. The era of the ever-cheaper budget model ended here first.

DeepSeek

• July 24, 2026 (scheduled): deepseek-chat and deepseek-reasoner aliases retired

• April 24, 2026: V4 launch. V4 Flash at $0.14 / $0.28 with 1M context, V4 Pro at $0.435 / $0.87

• September 29, 2025: V3.2-Exp launch, API prices cut more than 50%

• September 2025: V3.1 pricing consolidated, off-peak discounts removed

Trajectory: Down. Roughly 75% cheaper than 12 months ago while adding 1M context.

The AI Pricing Index

Google logged 6 price events in 12 months with its Flash tier up 5x, the first budget tier in the market to get materially more expensive. DeepSeek logged 4 events, down roughly 75%. If your product routes to whichever is cheapest, that routing table needs revisiting every couple of months.

The index counts documented list-price events per provider over the trailing 12 months, recounted monthly. Full methodology and all six provider timelines are on the AI Pricing Index.

What this means for your own pricing

If you build on Google, DeepSeek, or both, this pricing complexity becomes your pricing complexity. Four problems show up regardless of which side you pick.

• The margin problem. Every user interaction has variable cost. A power user generating long responses on a flagship model costs 10-50x more than a casual user on a value model. Per-seat pricing doesn't see this. You need usage-aware billing to protect margins.

• The model mix problem. Products route different requests to different models, and the table above shows the cost range that creates inside a single product. Your billing system needs to know which model served which request and price accordingly.

• The credit translation problem. Many AI products abstract provider costs with credit-based pricing. That means maintaining a conversion layer from usage to credits to dollars. Every provider price event forces you to re-derive the conversion rates.

• The visibility problem. Finance needs margin by customer, by feature, by model, by month. If your metering system lives apart from your billing system, that reconciliation happens in spreadsheets.

The index above adds the repricing angle: these two providers logged 10 price events in 12 months between them. Each one forces you to re-derive your own margins, credit conversion rates, and FX exposure if your revenue and your model bill sit in different currencies. Solvimon runs that layer: metering per provider, credits and wallets as first-class primitives, rate cards you update without an engineering sprint. See Solvimon for AI.

Related

• OpenAI vs Gemini pricing. OpenAI and Google token prices, plans, and repricing records.

• Anthropic vs DeepSeek pricing. A 23x flagship cost gap on the same workload.