Gemini vs DeepSeek V4 (2026)
Quick comparison
| Gemini (2.5 Flash-Lite / 3.1 Pro) | DeepSeek V4 | |
|---|---|---|
| Provider | DeepSeek | |
| Budget input cost | $0.10 / 1M (Flash-Lite) | $0.14 / 1M (Flash) |
| Budget output cost | $0.40 / 1M (Flash-Lite) | $0.28 / 1M (Flash) |
| Premium input cost | $2.00–4.00 / 1M (3.1 Pro, tiered) | Pro — self-host only |
| Context window | ~1,050,000 tokens | ~1,000,000 tokens |
| First-token latency | Low (Flash-Lite is tuned for it) | Depends on your hardware |
| Weights | Closed | Open, MIT licence |
| Self-hostable | No | Yes |
| Runs on | Google API, Vertex AI | Any API host, or your own GPUs |
Figures are approximate and current as of August 2026. Gemini 3.1 Pro pricing is tiered and rises above a 200K-token prompt — confirm the current bands with Google before you model costs.
Cost on a RAG-shaped workload
RAG prompts are lopsided: you stuff in a lot of retrieved context and get back a short answer. Here's 5,000 requests a day at 8,000 input tokens and 500 output tokens each:
| Model | Per day | Per month |
|---|---|---|
| Gemini 2.5 Flash-Lite | ~$5.00 | ~$150 |
| DeepSeek V4 (Flash API) | ~$6.30 | ~$189 |
| Gemini 3.1 Pro | ~$110 | ~$3,300 |
The two budget options are within a coffee-per-day of each other. Flip the ratio — long answers, short prompts — and DeepSeek V4's cheaper output rate pulls ahead instead. Gemini 3.1 Pro is roughly 20x the cost of either, which is only defensible when a Flash-tier model is visibly getting the answer wrong.
Where Gemini fits better
You're already on Google Cloud
If your data sits in BigQuery or GCS and your auth is already wired through Google IAM, running inference through Vertex AI removes a pile of integration work. That convenience is a real part of the total cost.
Latency-sensitive retrieval
Flash-Lite is engineered for fast first-token times, which matters for live search and chat-over-docs where users are watching the response appear. See our RAG guide for how much this shapes model choice.
Long prompts, short answers
Flash-Lite's $0.10 input rate is the lowest on our cost ranking. When 90% of your tokens are retrieved context, that input price is most of your bill.
Where DeepSeek V4 fits better
Data can't leave your infrastructure
Regulated industries, confidential matters, on-prem requirements — DeepSeek V4's MIT weights make it the only one of the two you can run in a closed environment. Our legal and finance guides cover where this is non-negotiable.
Long generated output
DeepSeek V4 Flash charges $0.28 per million output tokens against Flash-Lite's $0.40. For summarisation that produces multi-paragraph results, or agent steps that write a lot, that gap adds up.
No vendor lock-in
Open weights mean you can move hosts, negotiate with providers, or bring inference in-house later without a rewrite. That optionality has value even if you never use it.
Head-to-head by use case
| Use case | Better pick | Why |
|---|---|---|
| RAG on public data, hosted | Gemini 2.5 Flash-Lite | Lowest input price, low latency |
| RAG on confidential data | DeepSeek V4 | Self-hostable |
| Long-form summarisation | DeepSeek V4 | Cheaper output tokens |
| Live chat-over-docs | Gemini 2.5 Flash-Lite | Faster first token on the API |
| Highest answer quality | Gemini 3.1 Pro | Frontier tier, at frontier cost |
| Already on Vertex AI | Gemini | Integration already done |
| Avoiding lock-in | DeepSeek V4 | Open weights, portable |
So which one?
Pick Gemini if:
- Your infrastructure is already Google Cloud
- Prompts are long, answers are short, latency matters
- You want the lowest hosted input price available
- You occasionally need to escalate to a frontier model (3.1 Pro) without changing vendors
Pick DeepSeek V4 if:
- Data has to stay on your own hardware
- Your outputs are long and output pricing dominates
- You want to keep the option to switch hosts or self-host
- You're standardising one open model across several workloads
The common setup: Flash-Lite or DeepSeek V4 Flash for the everyday retrieval traffic, with a smaller path to Gemini 3.1 Pro or Claude Sonnet 5 for the queries where a weak answer actually costs you something.
FAQ
Is Gemini or DeepSeek V4 cheaper for RAG?
Gemini 2.5 Flash-Lite ($0.10 / $0.40 per million tokens) and DeepSeek V4 Flash ($0.14 / $0.28) are close enough that workload shape decides it. Flash-Lite wins on long prompts with short answers; DeepSeek V4 wins when answers are long. Gemini 3.1 Pro costs far more and is only worth it when answer quality is the bottleneck.
Do they have similar context windows?
Yes — both land around a million tokens, roughly 1.05M for Gemini and 1M for DeepSeek V4. For most RAG and summarisation work, retrieval quality and cost bind before window size does.
Can DeepSeek V4 be self-hosted and Gemini can't?
Correct. DeepSeek V4's weights are MIT-licensed. Gemini runs only through Google's API and Vertex AI. If data must stay on your own infrastructure, DeepSeek V4 is the only option here.
Which has lower latency?
Gemini 2.5 Flash-Lite is tuned for low first-token latency and usually feels faster on the hosted API. Self-hosted DeepSeek V4 latency is whatever your hardware and batching give you.