Gemini 2.5 Flash-Lite
- Input
- $0.200
- Output
- $0.160400,000 tokens
- Input
- $0.10 / 1M2,000,000 tokens
- Output
- $0.40 / 1M
- Context window
- 1,000,000Last updated: 2026-10-20
GPT-6 and GPT-5 per-token rates, Batch API 50% off, and prompt-cache savings — compared to Claude, Gemini, and DeepSeek.
Last updated: 2026-10-20
Released 2026-10-19; $0.15 / $0.60 / $0.015 (¥1 / ¥4 / ¥0.1). Flat rate — no long-context tier, and unlike M3 it does not accept service_tier=priority.
Checkpoint DeepSeek-V4.1-Flash-1017 (released 2026-10-17), served under the API model name `deepseek-flash`; open weights on Hugging Face / ModelScope. The 2026-09-10 launch price is unchanged. The launch checkpoint is kept as its own row (deepseek-flash-0910).
Released 2026-06-01. service_tier=priority costs 1.5× ($0.45 / $1.80 / $0.09). No separate cache-write charge. The cached-input rate above 512k doubles to $0.12; cost.ts applies the input multiplier to the cached rate as well.
Introductory pricing: $0.75 / $3.75 / $0.075 through 2026-12-31, then $1.50 / $7.50 / $0.15 from 2027-01-01.
Introductory pricing: $2 / $10 / $0.10 through 2026-11-30, then $4 / $20 / $0.20 from 2026-12-01. Implicit caching only — explicit caching is not supported. Batch and Flex run at half the standard rate; Priority is 1.8×.
Promotional pricing ($4 / $20 / $0.40) is available at least through 2026-11-21; the pre-promo rate was $5 / $30. Re-check after that date.
Prices verified 2026-10-20. Source: official provider pricing pages. · Machine-readable: /api/prices.json
OpenAI's Batch API processes requests asynchronously with a 24-hour SLA at half the standard rate — both input and output bill at 50%. You submit a JSONL file of requests, poll for completion, and there are no rate limits on the queue. Ideal for non-urgent workloads: evals, bulk summarization, dataset generation, and large backfills.
50% off · 24-hour SLA · no queue rate-limits
OpenAI automatically caches prompt prefixes (≥1,024 tokens) for 5–10 minutes (longer on GPT-5/6). Cached reads bill at roughly 10% of the standard input rate. For repeat-prefix workloads (system prompts, tool schemas, large documents) caching is the single biggest cost lever — most production stacks see a 50–80% input reduction once caching is on.
Compare prices across OpenAI, Claude, Gemini, DeepSeek, MiniMax, and Grok. Real tokenizer for OpenAI, accurate estimates for the rest.
OpenSee what your tokens actually cost after the OpenRouter markup — and when going direct to the provider is cheaper.
OpenCost per token and monthly estimates for Claude Opus, Sonnet, and Haiku — with the Anthropic API.
OpenV4-Pro and V4.1-Flash per-token rates, off-peak hours, and prompt-cache savings — compared to Claude, GPT, and Gemini.
Open