Gemini 3.5 Flash vs GPT-5.3-Codex
Gemini 3.5 Flash (2026) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. Gemini 3.5 Flash ships a 1.05m-token context window, while GPT-5.3-Codex ships a 400k-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 7 pts. On pricing, Gemini 3.5 Flash costs $1.50/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Gemini 3.5 Flash is standalone API model, while GPT-5.3-Codex is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Gemini 3.5 Flash | GPT-5.3-Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1.05m | 400k |
| Cheapest output | $9/1M tokens | $14/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | 3 shared | SWE-bench Verified leader |
Decision tradeoffs
- Gemini 3.5 Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3.5 Flash has the lower cheapest tracked output price at $9/1M tokens.
- Gemini 3.5 Flash has broader tracked provider coverage for fallback and procurement flexibility.
- Gemini 3.5 Flash uniquely exposes Multimodal in local model data.
- Local decision data tags Gemini 3.5 Flash for Coding, RAG, and Agents.
- GPT-5.3-Codex holds a shared-benchmark lead on SWE-bench Verified, ahead by 7 points.
- GPT-5.3-Codex uniquely exposes Computer use in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemini 3.5 Flash
$3,450
Cheapest tracked route/tier: Google AI Studio
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,450. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.3-Codex is $5/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Multimodal before moving production traffic.
- GPT-5.3-Codex adds Computer use in local capability data.
- Provider overlap exists on Vercel AI Gateway and OpenRouter; start route-level A/B tests there.
- Gemini 3.5 Flash is $5/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Computer use before moving production traffic.
- Gemini 3.5 Flash adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-05-19 | 2026-02-05 |
| Context window | 1.05m | 400k |
| Parameters | — | — |
| Architecture | Decoder Only | Decoder Only |
| License | Proprietary | Proprietary |
| Openness | Proprietary | Proprietary |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2025-01 | 2025-08 |
Pricing and availability
| Pricing attribute | Gemini 3.5 Flash | GPT-5.3-Codex |
|---|---|---|
| Input price | $1.50/1M tokens | $1.75/1M tokens |
| Output price | $9/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 3.5 Flash | GPT-5.3-Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | Yes |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 3.5 Flash | GPT-5.3-Codex |
|---|---|---|
| SWE-bench Verified | 78.0 | 85.0 |
| SWE-bench Pro | 55.1 | 56.8 |
| Terminal-Bench 2.0 | 76.2 | 77.3 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has Gemini 3.5 Flash at 78 and GPT-5.3-Codex at 85, with GPT-5.3-Codex ahead by 7 points; SWE-bench Pro has Gemini 3.5 Flash at 55.1 and GPT-5.3-Codex at 56.8, with GPT-5.3-Codex ahead by 1.7 points; Terminal-Bench 2.0 has Gemini 3.5 Flash at 76.2 and GPT-5.3-Codex at 77.3, with GPT-5.3-Codex ahead by 1.1 points. The largest visible gap is 7 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on multimodal input: Gemini 3.5 Flash. Both models share vision, reasoning mode, 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 3.5 Flash lists $1.50/1M input and $9/1M output tokens on the cheapest tracked provider, while GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 3.5 Flash lower by about $1.68 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.
Choose Gemini 3.5 Flash when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose GPT-5.3-Codex when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash supports 1.05m tokens, while GPT-5.3-Codex supports 400k 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 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash is cheaper on tracked token pricing. Gemini 3.5 Flash costs $1.50/1M input and $9/1M output tokens. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 3.5 Flash or GPT-5.3-Codex open source?
Gemini 3.5 Flash is listed under Proprietary. GPT-5.3-Codex 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 3.5 Flash or GPT-5.3-Codex?
Both Gemini 3.5 Flash and GPT-5.3-Codex expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 3.5 Flash and GPT-5.3-Codex?
Gemini 3.5 Flash is available on Google AI Studio, GCP Vertex AI, Vercel AI Gateway, and OpenRouter. GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.