Head-to-Head Model Comparison

o1-mini 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 o1-mini by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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OpenAI

o1-mini

Compact Reasoner

A cheap, fast reasoning model focused on coding, mathematics and STEM problem solving.

Intelligence Index44 / 100
Input Token:

$1.10 / 1M

Output Token:

$4.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

44%

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

  • o1-mini is 3.8x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • o1-mini is faster at 90 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 44.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo1-miniClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4494
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$1.10 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$4.40 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.05 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
90 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
44%84.6%
GPQA Diamond
Graduate-level reasoning
68.5%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.55 / 1M$0.40 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Claude Opus 5.5
+40.6% SWE-bench lead
Cost
o1-mini
3.8x cheaper monthly runtime
Speed
o1-mini
+15% faster generation
Context
Claude Opus 5.5
1M tokens window

Empirical Head-to-Head Benchmark Scores

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

o1-miniClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

44%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

68.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

79%vs91.5%
LMSYS Chatbot Arena Elo

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

1330ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

8.6%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

30.5%vs66.4%
SciCode (Scientific Computing)

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

36%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

60.5%vs83.1%
AIME (Advanced Math Competition)

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

88%vs95.4%
Long-Context Reasoning

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

70.5%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 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
o1-mini2.20s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
o1-mini7.76s
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)
o1-mini Monthly API Bill
$6.44 / month
$1.1/1M in · $4.4/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
o1-mini saves approximately $18.16 / month (74%) under this workload.3.8x Savings

o1-mini · Strengths & Key Advantages

  • Reasoning capability at a fraction of o1 pricing
  • Fast on competitive coding and maths problems
  • Long 65K output budget for extended derivations
  • Cheapest way to get genuine chain-of-thought reasoning
Considerations & Trade-offs
  • No vision support — text only
  • Limited broad world knowledge
  • Clearly weaker than o1 and o3 on hard multi-step tasks

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.

Metrico1-miniClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.85$3.85
Output Tokens / Task
Tokens generated per task
45K68K
Reasoning Tokens / Task
Thinking tokens burned per task
26K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

Featureo1-miniClaude Opus 5.5
Official API Model ID (SDK)o1-miniclaude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-092026-09
Knowledge CutoffOctober 2023June 2026
ArchitectureReasoning transformer with hidden chain-of-thoughtExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1.1/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.55/1M (no extra cache-write fee)$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)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 & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedAnthropic 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 Modalitiestexttext, vision
Output Modalitiestexttext

o1-mini vs Claude Opus 5.5: Quick Answers

Which is more intelligent, o1-mini or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 44 on the composite Intelligence Index.

Which model is faster?

o1-mini is faster, generating 90 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

o1-mini is cheaper at $1.05 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Opus 5.5 has lower latency, with a time to first token of 1.40s compared with 2.20s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdict

Choose o1-mini for budget stem and coding reasoning where cost matters, 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: o1-mini or Claude Opus 5.5?+

o1-mini costs $1.1/1M input and $4.4/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: o1-mini or Claude Opus 5.5?+

o1-mini supports 128K 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: OpenAI & Anthropic Official Documentation