Gemini 2.5 Flash vs Gemini 3.5 Flash
Gemini 2.5 Flash (2025) and Gemini 3.5 Flash (2026) are frontier reasoning models from Google DeepMind. Gemini 2.5 Flash ships a 1M-token context window, while Gemini 3.5 Flash ships a 1M-token context window. On pricing, Gemini 2.5 Flash costs $0.3/1M input tokens versus $1.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Gemini 2.5 Flash is ~400% cheaper at $0.3/1M; pay for Gemini 3.5 Flash only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Flash | Gemini 3.5 Flash |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1M | 1M |
| Cheapest output | $2.5/1M tokens | $9/1M tokens |
| Provider routes | 4 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemini 2.5 Flash has the lower cheapest tracked output price at $2.5/1M tokens.
- Gemini 2.5 Flash has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Gemini 2.5 Flash for Coding, RAG, and Agents.
- Gemini 3.5 Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3.5 Flash uniquely exposes Reasoning in local model data.
- Local decision data tags Gemini 3.5 Flash for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemini 2.5 Flash
$865
Cheapest tracked route: Google AI Studio
Gemini 3.5 Flash
$3,450
Cheapest tracked route: Google AI Studio
Estimated monthly gap: $2,585. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Google AI Studio and GCP Vertex AI; start route-level A/B tests there.
- Gemini 3.5 Flash is $6.5/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 3.5 Flash adds Reasoning in local capability data.
- Provider overlap exists on Google AI Studio and GCP Vertex AI; start route-level A/B tests there.
- Gemini 2.5 Flash is $6.5/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2026-05-19 |
| Context window | 1M | 1M |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-01 | 2025-01 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Flash | Gemini 3.5 Flash |
|---|---|---|
| Input price | $0.3/1M tokens | $1.5/1M tokens |
| Output price | $2.5/1M tokens | $9/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Flash | Gemini 3.5 Flash |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Gemini 3.5 Flash. Both models share vision, multimodal input, function calling, and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemini 2.5 Flash lists $0.3/1M input and $2.5/1M output tokens, while Gemini 3.5 Flash lists $1.5/1M input and $9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 2.5 Flash lower by about $2.79 per million blended tokens. Availability is 4 providers versus 2, so concentration risk also matters.
Choose Gemini 2.5 Flash when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Gemini 3.5 Flash when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Gemini 2.5 Flash or Gemini 3.5 Flash?
Gemini 3.5 Flash supports 1M tokens, while Gemini 2.5 Flash supports 1M tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 2.5 Flash or Gemini 3.5 Flash?
Gemini 2.5 Flash is cheaper on tracked token pricing. Gemini 2.5 Flash costs $0.3/1M input and $2.5/1M output tokens. Gemini 3.5 Flash costs $1.5/1M input and $9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Flash or Gemini 3.5 Flash open source?
Gemini 2.5 Flash is listed under Proprietary. Gemini 3.5 Flash is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemini 2.5 Flash or Gemini 3.5 Flash?
Both Gemini 2.5 Flash and Gemini 3.5 Flash expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Gemini 2.5 Flash or Gemini 3.5 Flash?
Both Gemini 2.5 Flash and Gemini 3.5 Flash expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Gemini 2.5 Flash and Gemini 3.5 Flash?
Gemini 2.5 Flash is available on Google AI Studio, GCP Vertex AI, Replicate API, and OpenRouter. Gemini 3.5 Flash is available on Google AI Studio and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.