LLM Reference

Gemini 2.0 Flash vs GPT-5.5

Gemini 2.0 Flash (2025) and GPT-5.5 (2026) are frontier-tier reasoning models from Google DeepMind and OpenAI. Gemini 2.0 Flash ships a 2m-token context window, while GPT-5.5 ships a 1.05m-token context window. On MMLU PRO, GPT-5.5 leads by 10.2 pts. On pricing, Gemini 2.0 Flash costs $0.10/1M input tokens; GPT-5.5 ranges from $5 to $10/1M input tokens by tier. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

GPT-5.5 is safer overall; choose Gemini 2.0 Flash when coding workflow support matters.

Decision scorecard

Local evidence first
SignalGemini 2.0 FlashGPT-5.5
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window2m1.05m
Cheapest output$0.40/1M tokens$30/1M tokens
Provider routes4 tracked3 tracked
Shared benchmarks1 rowsMMLU PRO leader

Decision tradeoffs

Choose Gemini 2.0 Flash when...
  • Gemini 2.0 Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Gemini 2.0 Flash has the lower cheapest tracked output price at $0.40/1M tokens.
  • Gemini 2.0 Flash has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Gemini 2.0 Flash for Coding, RAG, and Agents.
Choose GPT-5.5 when...
  • GPT-5.5 leads the largest shared benchmark signal on MMLU PRO by 10.2 points.
  • Local decision data tags GPT-5.5 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.

Lower estimate Gemini 2.0 Flash

Gemini 2.0 Flash

$180

Cheapest tracked route/tier: OpenRouter

GPT-5.5

$11,500

Cheapest tracked route/tier: OpenAI API 0-272K input tokens

Estimated monthly gap: $11,320. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Gemini 2.0 Flash -> GPT-5.5
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • GPT-5.5 is $29.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
GPT-5.5 -> Gemini 2.0 Flash
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Gemini 2.0 Flash is $29.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2025-01-302026-04-23
Context window2m1.05m
Parameters
Architecture-decoder only
LicenseGemini Terms of ServiceProprietary
Knowledge cutoff2025-042025-12

Pricing and availability

Pricing attributeGemini 2.0 FlashGPT-5.5
Input price$0.10/1M tokens
0-272K input tokens
$5/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
0-272,000t
$5/1M tokens
272K+ input tokens
$8/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
272,000t+
$10/1M tokens
Output price$0.40/1M tokens
0-272K input tokens
$30/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
0-272,000t
$30/1M tokens
272K+ input tokens
$36/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
272,000t+
$45/1M tokens
Providers

Capabilities

CapabilityGemini 2.0 FlashGPT-5.5
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGemini 2.0 FlashGPT-5.5
MMLU PRO77.988.1

Deep dive

On shared benchmark coverage, MMLU PRO has Gemini 2.0 Flash at 77.9 and GPT-5.5 at 88.1, with GPT-5.5 ahead by 10.2 points. The largest visible gap is 10.2 points on MMLU PRO, 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 is close: both models cover vision, multimodal input, reasoning mode, function calling, and tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, Gemini 2.0 Flash lists $0.10/1M input and $0.40/1M output tokens on the cheapest tracked provider, while GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 0-272,000t is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output; 272,000t+ is $10/1M input and $45/1M output. A 70/30 input-output blend puts Gemini 2.0 Flash lower by about $12.31 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 3, so concentration risk also matters.

Choose Gemini 2.0 Flash when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose GPT-5.5 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 2.0 Flash or GPT-5.5?

Gemini 2.0 Flash supports 2m tokens, while GPT-5.5 supports 1.05m 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 2.0 Flash or GPT-5.5?

Gemini 2.0 Flash lists $0.10/1M input and $0.40/1M output tokens on the cheapest tracked provider. GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 0-272,000t is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output; 272,000t+ is $10/1M input and $45/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is Gemini 2.0 Flash or GPT-5.5 open source?

Gemini 2.0 Flash is listed under Gemini Terms of Service. GPT-5.5 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 2.0 Flash or GPT-5.5?

Both Gemini 2.0 Flash and GPT-5.5 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 2.0 Flash or GPT-5.5?

Both Gemini 2.0 Flash and GPT-5.5 expose multimodal input. 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.

Where can I run Gemini 2.0 Flash and GPT-5.5?

Gemini 2.0 Flash is available on OpenRouter, Google AI Studio, GCP Vertex AI, and Vercel AI Gateway. GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.