GPT-5.5 vs Claude Opus 4.7 vs Gemini 3.5 2026 Compared

Two of these three are flagships and one is a fast agent-tier model, which is exactly why a naive per-token comparison of GPT-5.5, Claude Opus 4.7, and Gemini 3.5 Flash misleads. They sit at different tiers and price very differently. This article puts the verified API rates side by side, explains the context-window and tokenizer traps, and works a concrete monthly cost.

1. Headline API prices

Prices verified against each vendor's API pricing page as of May 26, 2026, per million tokens.

Model	Input	Output	Tier / context
GPT-5.5	$5.00[1]	$30.00[1]	Flagship, 1M context[1]
Claude Opus 4.7	$5.00[2]	$25.00[2]	Flagship, 1M context (no premium)[2]
Gemini 3.5 Flash	$1.50[3]	$9.00[3]	Fast agent-tier (cache $0.15)[3]

Two things stand out. Among the flagships, Opus 4.7 and GPT-5.5 match on input ($5) but Opus is cheaper on output ($25 vs $30), where most spend concentrates in generation-heavy workloads^[1][2]. And Gemini 3.5 Flash sits far below both at $1.50/$9.00, but it is a fast agent-tier model, not a flagship, so it is not a straight substitute^[3].

2. Context windows and the tokenizer trap

All three offer large context, but the cost mechanics differ. GPT-5.5 and Opus 4.7 both reach 1M tokens, and Opus 4.7 notably charges the same per-token rate across its full 1M window with no long-context premium^[1][2].

The trap is the tokenizer. Claude Opus 4.7 ships a new tokenizer that can produce up to around 35% more tokens for the same input text than the prior Opus generation^[4]. Identical per-token rates do not mean identical cost: the same document can tokenize to different counts across models, so a cost comparison based only on sticker rates is incomplete. When you benchmark cost, measure the actual token count each model produces for your real prompts, then multiply by the rate. Use the token cost optimization playbook to keep counts down.

3. What each is positioned to win

• GPT-5.5 is positioned for ultra-long-context tasks, where vendor benchmarks claim a strong lead on summarizing large codebases and long document corpora^[1]. Treat such benchmark claims as vendor-reported.
• Claude Opus 4.7 is positioned for top-tier reasoning and coding, with the cheaper flagship output rate and no long-context premium^[2].
• Gemini 3.5 Flash is positioned for fast, high-throughput agentic and coding work at a fraction of flagship cost, with a low cache rate ($0.15) that rewards repeated context^[3].

The honest framing: these are positioning and vendor claims, not independently verified results, and no benchmarks were run here. The decision should be tiered. Use Gemini 3.5 Flash where its tier clears your quality bar at far lower cost; step up to a flagship only for tasks that demonstrably need it. Among flagships, default to the cheaper-output Opus 4.7 unless GPT-5.5's long-context behavior measurably wins on your workload.

4. Worked cost example

A workload of 50M input plus 15M output tokens per month, API cost only, at each model's listed rate (token counts assumed equal for illustration; real counts vary by tokenizer):

Model	Input cost	Output cost	Monthly
GPT-5.5	$250[1]	$450[1]	$700
Claude Opus 4.7	$250[2]	$375[2]	$625
Gemini 3.5 Flash	$75[3]	$135[3]	$210

The arithmetic: 50M input × rate plus 15M output × rate. GPT-5.5 is (50 × $5) + (15 × $30) = $250 + $450 = $700; Opus 4.7 is $250 + $375 = $625, about $75 less, driven entirely by the cheaper output rate; Gemini 3.5 Flash is (50 × $1.50) + (15 × $9) = $75 + $135 = $210, roughly a third of either flagship. The flagship gap ($75/month here) is small relative to the tier gap ($400-plus) to Gemini 3.5 Flash. The biggest cost lever is choosing the right tier, not the right flagship. Adjust for tokenizer differences (Opus 4.7 may produce more tokens) and model the full stack with the AI stack cost calculator.

5. Decision guidance

• Task fits a fast agent tier: Gemini 3.5 Flash at $1.50/$9.00, roughly a third of flagship cost; verify quality on your prompts.
• Need flagship reasoning, output-heavy: Claude Opus 4.7 at $5/$25, the cheaper-output flagship with no long-context premium.
• Ultra-long-context summarization or large-corpus tasks: evaluate GPT-5.5, where its long-context behavior is positioned to win.
• Cost-critical: the tier choice (Flash vs flagship) matters far more than the flagship choice; and measure real token counts, not just rates.
• Repeated context: Gemini 3.5 Flash's $0.15 cache rate rewards caching the same context across calls.

Re-verify each pricing page before committing; model rates move with every release, and benchmark claims here are vendor-reported, not independently tested. For the cheap-tier deep dive, see the Gemini cost ladder and the cheapest LLM API ranking.

All pricing figures verified against official API pricing pages as of 2026-06-12. Anthropic's Opus flagship is now Claude Opus 4.8 (since 2026-05-28) at the same $5/$25 standard rate.

Frequently asked questions

Which is cheapest: GPT-5.5, Claude Opus 4.7, or Gemini 3.5 Flash?

On the API rate, Gemini 3.5 Flash is by far the cheapest at $1.50 per million input and $9.00 per million output tokens, against Claude Opus 4.7 at $5/$25 and GPT-5.5 at $5/$30, all verified May 2026. But Gemini 3.5 Flash is a fast agent-tier model, not a flagship, so it is not a like-for-like swap for the two top-end models. Among the flagships, Opus 4.7 ($5/$25) undercuts GPT-5.5 ($5/$30) on output, where most cost concentrates. If you can use Gemini 3.5 Flash's tier for the task, it is dramatically cheaper; if you need flagship reasoning, Opus 4.7 is the cheaper flagship.

Does Claude Opus 4.7 charge extra for its 1M context window?

No. Claude Opus 4.7 maintains the same per-token rate ($5 input, $25 output per million) across its full 1M-token context window, with no long-context premium, per Anthropic's pricing in May 2026. The catch is the tokenizer: Opus 4.7 ships a new tokenizer that can produce up to around 35% more tokens for the same input text than the prior Opus generation, which raises the actual cost despite identical per-token rates. So when comparing to GPT-5.5 or Gemini, account for token count, not just the per-token price, because the same document can tokenize to different counts across models.

Is Gemini 3.5 Flash a flagship like GPT-5.5 and Opus 4.7?

No. Gemini 3.5 Flash is a fast, agent-tier model, not a top-end flagship in the same class as GPT-5.5 and Claude Opus 4.7. Its $1.50/$9.00 pricing is well below the flagships, and the 'Flash' name refers to speed. Google has claimed it performs strongly on coding and agentic benchmarks, but treat that as a vendor claim pending independent confirmation. The honest comparison is tiered: use Gemini 3.5 Flash for high-throughput, latency-sensitive tasks where its tier suffices, and reserve GPT-5.5 or Opus 4.7 for tasks that genuinely need flagship reasoning quality.