Head-to-head
Gemini 3.5 Flash vs GPT-5.5: which AI model wins in 2026?
Gemini 3.5 Flash ($9.00/1M out) and GPT-5.5 ($30/1M out) are two of the most-used AI models in 2026. Across 3 community votes, GPT-5.5 leads with 57% approval.
Quick verdict
On Reasoning, pick GPT-5.5: the arena rates it 5/5 against 3.5/5 for Gemini 3.5 Flash. On budget, Gemini 3.5 Flash wins: it starts at $9.00/1M out versus $30/1M out for GPT-5.5.
Line-by-line comparison
Strengths and weaknesses
Gemini 3.5 Flash
- Beats Gemini 3.1 Pro on agentic benchmarks: 76.2% Terminal-Bench 2.1, 1656 Elo GDPval-AA (vs 1314 for 3.1 Pro), 83.6% MCP Atlas
- Artificial Analysis Intelligence Index 50 at high thinking effort, ranking #10 of 170 tracked models
- Very fast generation (~185 output tokens/sec per Artificial Analysis); Google claims 4x faster output than other frontier models
- 1M-token context window (1,048,576) with multimodal input: text, image, audio, video, PDF
- 25% cheaper than Gemini 3.1 Pro ($1.50/$9 vs $2/$12) while outperforming it on production agent workloads
- Adjustable thinking effort (minimal/low/medium/high) plus 50% batch discount and $0.15/1M context caching
- 3x price increase over Gemini 3 Flash ($0.50/$3.00) and 5-6x over 2.5 Flash; HN devs saw it as Google probing price tolerance
- Over-eager and verbose: devs report it ignores completion criteria and embellishes beyond instructions (compared to Claude's 'Sonnet 3.7 moment')
- Reliability complaints on Flash serving: developers report frequent 503 errors during peak periods
- Weaker on long-horizon agentic tasks with arbitrary tool availability, a recurring theme devs report with Google models
- High time-to-first-token (~23s at high thinking effort per Artificial Analysis), poor fit for latency-sensitive chat
GPT-5.5
- 1M-token context window (1,050,000) with 128K max output and reasoning effort tunable from none to xhigh
- State-of-the-art ARC-AGI-2 at 85.0% (vs 73.3% for GPT-5.4) and Terminal-Bench 2.0 at 82.7%
- Strong agentic coding autonomy: devs report it one-shots tasks that took GPT-5.4 multiple turns and fixes its own mistakes; +50 points on Code Arena vs GPT-5.4
- Aggressive discounts: 90% off cached input ($0.50/1M) and 50% off via Batch or Flex ($2.50/$15)
- Fast for a frontier reasoner: devs say it is the first GPT model comfortable to run at medium or low thinking effort
- List price doubled vs GPT-5.4 ($5/$30 vs $2.50/$15) for the same 1M-token context window
- Overly literal instruction-following: devs report it fails to infer intent in obvious places where Claude succeeds
- Trails Claude Opus 4.8 on SWE-bench Pro (58.6% vs 69.2%); HN developers still favor Claude roughly 2:1 for coding
- Sometimes too conservative with code changes or skips deep reasoning entirely, answering immediately on complex prompts
- Long-context surcharge: prompts over 272K input tokens are billed 2x input and 1.5x output for the whole session
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on Gemini 3.5 Flash
Pick Gemini 3.5 Flash if you run agentic coding or high-volume multimodal pipelines and want near-Pro quality at 4x the speed: it actually beats Gemini 3.1 Pro on Terminal-Bench and GDPval while costing 25% less. Avoid it if you used the Flash line as a budget tier, since it costs 3x its predecessor Gemini 3 Flash, which remains the cheap option at $0.50/$3.00. Also skip it for latency-sensitive chat at high thinking effort (~23s to first token) or strict, no-embellishment output where its verbosity works against you.
The arena’s verdict on GPT-5.5
Pick GPT-5.5 over GPT-5.4 if you need stronger agentic autonomy, terminal-heavy workflows, or SOTA abstract reasoning, but know the list price doubled from GPT-5.4's $2.50/$15 to $5/$30 while the 1M-token context stayed the same. Teams doing high-stakes multi-file refactoring may still prefer Claude Opus, which leads SWE-bench Pro (69.2% vs 58.6%) and infers intent better from loose prompts. Budget-sensitive users should mind the 272K-token surcharge and reports of faster limit burn, and lean on caching, Batch, or Flex to halve costs.
What the crowd says
On Gemini 3.5 Flash
No verdicts yet. Be the first to speak.
On GPT-5.5
“It is painfully literal. Where Claude infers intent in obvious places, 5.5 wants everything spelled out. And the price doubled vs 5.4 for the same 1M context.”
“85 on ARC-AGI-2 and you can feel it. Stuff that used to stall my agent just resolves now. 1M context with 128K output covers every workflow I have.”
“5.5 one-shots tasks that took 5.4 three turns, and it fixes its own mistakes mid-run instead of doubling down. The reasoning effort dial from none to xhigh is genuinely useful.”
Keep comparing
Frequently asked questions
Is Gemini 3.5 Flash better than GPT-5.5?
The crowd currently sides with GPT-5.5: 57% recommend it, versus 50% for Gemini 3.5 Flash (3 votes). On Reasoning, GPT-5.5 rates higher (5/5 vs 3.5/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, Gemini 3.5 Flash or GPT-5.5?
Gemini 3.5 Flash is cheaper: it starts at $9.00/1M out, while GPT-5.5 starts at $30/1M out.
How much do Gemini 3.5 Flash and GPT-5.5 cost per 1M tokens?
Gemini 3.5 Flash: $1.50/1M in per 1M input tokens, $9.00/1M out per 1M output tokens. GPT-5.5: $5/1M in per 1M input tokens, $30/1M out per 1M output tokens.