Head-to-Head Model Comparison

Gemini 2.5 Flash vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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Compare Gemini 2.5 Flash by Google against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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Google

Gemini 2.5 Flash

Fast Workhorse

Balanced workhorse combining low latency and cost with capable chain-of-thought reasoning.

Intelligence Index68 / 100
Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Anthropic

Claude Opus 5.5

Frontier Intelligence Titan

Anthropic's most intelligent model for complex reasoning, research, and strategic analysis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Key Differences at a Glance

  • Gemini 2.5 Flash is 8.7x cheaper for API usage (input + output tokens combined).
  • Gemini 2.5 Flash has a larger context window (1M vs 1M tokens).
  • Gemini 2.5 Flash is faster at 160 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 58.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.5 FlashClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
6894
Provider
GoogleAnthropic
Input Price
Cost per million input tokens
$0.30 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$2.50 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.36 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
160 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
58.2%84.6%
GPQA Diamond
Graduate-level reasoning
75.4%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.07 / 1M$0.40 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Claude Opus 5.5
+26.4% SWE-bench lead
Cost
Gemini 2.5 Flash
8.7x cheaper monthly runtime
Speed
Gemini 2.5 Flash
+105% faster generation
Context
Gemini 2.5 Flash
1.05M tokens window

Empirical Head-to-Head Benchmark Scores

Official evaluation metrics verified by independent third-party research labs.

Gemini 2.5 FlashClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

58.2%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

75.4%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

83.2%vs91.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1385ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

84.5%vs95.4%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs78 tok/s

Latency & Response Time

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Gemini 2.5 Flash0.45s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.5 Flash3.58s
Claude Opus 5.57.81s

Real-Time Interactive Token Cost Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Gemini 2.5 Flash Monthly API Bill
$2.81 / month
$0.3/1M in · $2.5/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Gemini 2.5 Flash saves approximately $21.79 / month (89%) under this workload.8.7x Savings

Gemini 2.5 Flash · Strengths & Key Advantages

  • Fast execution speed with optional thinking mode
  • 1M context with audio and video ingestion
  • High cost-to-performance ratio
Considerations & Trade-offs
  • Secondary reasoning depth compared to 2.5 Pro
  • Token consumption increases under deep thinking

Claude Opus 5.5 · Strengths & Key Advantages

  • Unmatched autonomous multi-step agentic coding and refactoring
  • Flawless multi-document reasoning over 1M token context with no long-prompt surcharge
  • Highest composite Intelligence Index score measured (94/100), leading SWE-bench Verified at 84.6%
  • Precise tool execution with robust error-recovery loops
Considerations & Trade-offs
  • Premium output pricing ($20.00/M) plus heavy reasoning-token usage (~68K output tokens per complex task) keeps long agentic runs expensive
  • Long thinking times at maximum effort can push a single hard agentic task toward ~$3.85+

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGemini 2.5 FlashClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.85$3.85
Output Tokens / Task
Tokens generated per task
32K68K
Reasoning Tokens / Task
Thinking tokens burned per task
14K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.5 FlashClaude Opus 5.5
Official API Model ID (SDK)models/gemini-2-5-flashclaude-opus-5-5-20260901
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-062026-09
Knowledge CutoffMarch 2025June 2026
ArchitectureHigh-throughput sparse multimodal transformer with thinking modeExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.075/1M with configurable TTL$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationGoogle DeepMind Frontier Safety Framework VerifiedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audio, videotext, vision
Output Modalitiestexttext

Gemini 2.5 Flash vs Claude Opus 5.5: Quick Answers

Which is more intelligent, Gemini 2.5 Flash or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 68 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash is faster, generating 160 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash is cheaper at $0.36 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash has lower latency, with a time to first token of 0.45s compared with 1.40s.

Which model has a larger context window?

Gemini 2.5 Flash has a larger context window, supporting 1.05M tokens compared with 1M tokens.

Verdict

Choose Gemini 2.5 Flash for production web applications, interactive agents, and multimodal media indexing, or choose Claude Opus 5.5 for large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis.

Frequently asked questions

Which is cheaper: Gemini 2.5 Flash or Claude Opus 5.5?+

Gemini 2.5 Flash costs $0.3/1M input and $2.5/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Gemini 2.5 Flash or Claude Opus 5.5?+

Gemini 2.5 Flash supports 1.0M tokens whereas Claude Opus 5.5 supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Sources: Google & Anthropic Official Documentation