GPT-5 vs Gemini 3.5 Flash: same budget, different machines

A few cents separate the rate cards. Everything that matters is in the engineering columns: speed, context, and the free tier.

By the benchr team · · View changelog · Figures verified against official sources, June 10, 2026

GPT-5 input / 1MOpenAI · output $10
Flash input / 1MGoogle · output $9
Flash throughputbenchr tracking · GPT-5: 90
Flash contextGPT-5: 400K

Two models, one budget, completely different machines. This is the rare comparison where you can ignore the rate card — a few cents per million tokens separates them in either direction depending on your input/output ratio. Everything that matters here is in the engineering columns.

Side-by-side specs

GPT-5 vs Gemini 3.5 Flash — verified figures, June 10, 2026
DimensionGPT-5Gemini 3.5 Flash
Input / 1M$1.25$1.50
Output / 1M$10.00$9.00
Cached input / 1M$0.15
Free API tierNoYes
Context window400,0001,048,576
Max output128,00065,536
First token (benchr est.)520ms195ms
Throughput (benchr est.)90 tok/s289 tok/s

Speed is Flash's whole pitch

At 195ms to first token and 289 tokens/second in benchr's tracking, Flash is one of the fastest frontier-tier models on the market — about 3× GPT-5's throughput. For user-facing chat, live coding assistants, and any product where someone watches the answer stream, that difference is visible to the naked eye. A 2,000-token answer takes roughly 7 seconds to stream on Flash and 22 on GPT-5. No price discount buys back fifteen seconds of a user's attention.

Where GPT-5 holds the line

Output ceiling and ecosystem. GPT-5's 128K max output doubles Flash's 64K — relevant for long code generations and document drafting in one call. And the integration story repeats from every OpenAI comparison: more frameworks, more battle-tested function calling, more drop-in compatibility. On coding, benchr tracks Flash at 80.6% SWE-bench Verified against GPT-5's official 74.9% — read that gap as directional, since the Flash figure is an editorial estimate in benchr's index, flagged as such, while GPT-5's is official. The Flash review has the fuller picture.

The free-tier wrinkle

Flash has a free API tier; GPT-5 doesn't. For prototyping, internal tools, and low-volume side projects, that's not a rounding error — it's the entire bill. Plenty of teams should prototype on Flash's free tier, measure, and only then decide where paid traffic goes. The free-AI roundup maps where the free tier taps out.

Frequently asked

GPT-5 and Gemini 3.5 Flash cost almost the same — what's the real difference?

Shape, not price. Flash is built for speed and scale: roughly 195ms to first token and 289 tokens/second in benchr's tracking, about three times GPT-5's throughput, with Gemini 3.5 Flash's 1M context window against GPT-5's 400K. GPT-5 is the steadier generalist with deeper ecosystem support. At $1.25/$10 vs $1.50/$9 per million, price won't decide this one.

Which is cheaper for a chat application?

Nearly identical. A chat turn with 2K input and 500 output tokens costs about $0.0075 on either model. Flash pulls ahead on input-heavy RAG thanks to Gemini 3.5 Flash's $0.15/1M cached-input tier and a free API tier for prototyping; GPT-5 edges ahead on prompt-heavy mixes where its lower $1.25 input rate dominates. The deciding factors are speed and context, not the bill.

Does Gemini 3.5 Flash really beat GPT-5 on coding?

benchr tracks Flash at 80.6% SWE-bench Verified versus GPT-5's official 74.9% — but note the Flash figure is an editorial estimate in benchr's data, marked as such, while GPT-5's is official. Treat the gap as directional, and test on your own tasks.

Changelog

  • June 10, 2026 — Expanded from a spec table into a full comparison: cost math on a concrete workload, where each model wins, and a verdict. Page re-indexed.
  • June 6, 2026 — Published as a spec-table stub (noindexed pending expansion).

Sources

  • OpenAI API pricing — openai.com/api/pricing (verified June 10, 2026)
  • Google Gemini API pricing — ai.google.dev/gemini-api/docs/pricing (verified June 10, 2026)
  • benchr model-figures.json — the verified figure record (June 10, 2026)