DeepSeek V4.1 Flash vs Gemini 3.5 Flash-Lite
Side-by-side comparison of API pricing, specs, benchmarks, and capabilities
DeepSeek V4.1 Flash is 38.2% cheaper on blended cost ($0.525 vs $0.850/Mtok)
| Specification |
by DeepSeek
|
by Google
|
|---|---|---|
| Overview | ||
| Status | Current budget | Current budget |
| Released | ||
| Pricing per million tokens | ||
| Input | $0.300/Mtok | $0.300/Mtok |
| Output | $1.20/Mtok | $2.50/Mtok |
| Blended avg | $0.525/Mtok | $0.850/Mtok |
| Cached input | $0.006/Mtok | $0.030/Mtok |
| Price basis | DeepSeek bills this model at TWO rates depending on the hour. The tracked figure is the PEAK rate: $0.30 input (cache miss) / $0.006 input (cache hit) / $1.20 output per 1M tokens. Off-peak is exactly half: $0.15 / $0.003 / $0.60. Peak hours are 01:00-04:00 and 06:00-10:00 UTC, Monday through Friday; every other hour, and all of Saturday and Sunday, is off-peak. Peak is the headline here because DeepSeek defines off-peak as half of peak rather than the other way round, so peak is the list rate, and because a caller who does not schedule around the clock needs the published number to be a ceiling rather than a floor. Halve it for a workload that runs entirely outside those hours. Third-party catalogues that quote this model at $0.15/$0.60 per 1M are printing the OFF-PEAK tier, not a different rate card. | Verified against Google's Gemini API pricing page (ai.google.dev) on 2026-07-28: the Gemini 3.5 Flash-Lite Standard paid tier is $0.30/1M input, $2.50/1M output, $0.03/1M context caching (batch tier $0.15/$1.25). The identical $0.30/$2.50 price shared with the deprecated Gemini 2.5 Flash reflects Google's uniform Flash tier pricing, not a placeholder — the value matches LiteLLM gemini/gemini-3.5-flash-lite. |
| Specifications | ||
| Context window | 1M tokens | 1M tokens |
| Parameters | Proprietary | Proprietary |
| Speed (TPS) | — | — |
| Modalities | ||
| Input |
textimage
|
textimageaudiovideo
|
| Benchmarks sources: public leaderboards / Artificial Analysis, Google DeepMind Gemini 3.5 Flash-Lite model card, LMSYS Chatbot Arena (UC Berkeley) | ||
| Terminal-Bench 2.1 | — | 54 vendor |
| OSWorld-Verified | — | 74 vendor |
| Independent composite scores each on its own scale — not part of the average above | ||
| AA Intelligence Index | — | 22.7 |
| AA Agentic Index | — | 15.9 |
| AA-Omniscience Index (−100–100) | — | 5.2 |
| GDPval-AA v2 | — | 1063.2 ELO |
| LMSYS Chatbot Arena | — | 1456.9 ELO |
| Providers | ||
| Available from |
DeepSeek — $0.300/$1.20/Mtok
|
Google — $0.300/$2.50/Mtok
|
Cost at scale
1M tokens · 50/50 input/output| Volume | DeepSeek V4.1 Flash | Gemini 3.5 Flash-Lite | Savings |
|---|---|---|---|
| 1M tokens | $0.52 | $0.85 | $0.33 (38.8%) |
| 10M tokens | $5.25 | $8.5 | $3.25 (38.2%) |
| 100M tokens | $52.5 | $85 | $32.5 (38.2%) |
| 1000M tokens | $525 | $850 | $325 (38.2%) |
When to pick which
distilled from the pricing and spec data above
Pick DeepSeek V4.1 Flash if…
- cost dominates: $0.525/Mtok blended vs $0.850 — 38.2% less on the same 50/50 token mix
- your workload re-reads context (agents, RAG, long chats): cached input costs $0.006/Mtok — 98% off its list input price
Pick Gemini 3.5 Flash-Lite if…
- this pairing gives Gemini 3.5 Flash-Lite no edge on price, context, cache discount, or measured performance — pick it only for qualitative fit (ecosystem, compliance, model behavior on your prompts)
Try DeepSeek V4.1 Flash on DeepSeek
The cheaper option here — DeepSeek V4.1 Flash costs $0.525/Mtok blended on DeepSeek.
Summary
DeepSeek V4.1 Flash by DeepSeek costs $0.300/Mtok input and $1.20/Mtok output, with a 1M-token context window. It supports text, image input.
Gemini 3.5 Flash-Lite by Google costs $0.300/Mtok input and $2.50/Mtok output, with a 1M-token context window. It supports text, image, audio, video input.
On a blended cost basis, DeepSeek V4.1 Flash is 38.2% cheaper than Gemini 3.5 Flash-Lite.
Note: Pricing is per million tokens. Actual costs vary with usage patterns, prompt caching, and batch discounts. Always verify against official provider pricing pages.
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