Head-to-Head Model Comparison

o4-mini vs Claude Haiku 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
o4-mini vs Claude Haiku 5.5: Benchmarks, Pricing & Speed Comparison

o4-mini by OpenAI and Claude Haiku 5.5 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Claude Haiku 5.5 holds a notable pricing advantage for token ingestion. On output generation, o4-mini is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 200K tokens. In latency-sensitive production environments, Claude Haiku 5.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

Head-to-Head Comparison

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o4-mini

Fast Compact Reasoner

A fast o-series model combining compact reasoning with coding and tool use.

Intelligence Index50 / 100
Input Token:

$1.10 / 1M

Output Token:

$4.40 / 1M

Context Window:

200K tokens

SWE-bench Verified:

57.5%

Anthropic

Claude Haiku 5.5

Fast 5.5 Lane

The ultra-rapid, low-cost powerhouse of late 2026, bringing fast reasoning, 200K context, and near-instant response speeds to customer agents and real-time pipelines.

Intelligence Index62 / 100
Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

68.4%

Key Differences at a Glance

  • o4-mini is 1.0x cheaper for API usage (input + output tokens combined).
  • Claude Haiku 5.5 is faster at 160 tok/s vs 105 tok/s.
  • Claude Haiku 5.5 leads on SWE-bench coding (68.4% vs 57.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo4-miniClaude Haiku 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5062
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$1.10 / 1M$1.00 / 1M
Output Price
Cost per million output tokens
$4.40 / 1M$5.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.85 / 1M$0.77 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
100K64K
Throughput Speed
Tokens generated per second
105 tok/s160 tok/s
SWE-bench Verified
Real-world software engineering
57.5%68.4%
GPQA Diamond
Graduate-level reasoning
73%69.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.28 / 1M$0.10 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Claude Haiku 5.5
+10.9% SWE-bench lead
Cost
o4-mini
1.0x cheaper monthly runtime
Speed
Claude Haiku 5.5
+52% faster generation
Context
Tied
200K tokens window

Empirical Head-to-Head Benchmark Scores

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

o4-miniClaude Haiku 5.5
SWE-bench Verified (Autonomous Coding)

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

57.5%vs68.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

73%vs69.8%
MMLU-Pro (Multi-task Language Understanding)

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

83%vs83.2%
LMSYS Chatbot Arena Elo

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

1325ptsvs1370pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.2%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

36%vsN/A
SciCode (Scientific Computing)

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

38.5%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vsN/A
AIME (Advanced Math Competition)

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

89.5%vsN/A
Long-Context Reasoning

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

74.5%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs160 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
o4-mini1.80s
Claude Haiku 5.50.22s
Est. End-to-End Response (500 tokens)TTFT + generation time
o4-mini6.56s
Claude Haiku 5.53.35s

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)
o4-mini Monthly API Bill
$6.02 / month
$1.1/1M in · $4.4/1M out
Claude Haiku 5.5 Monthly API Bill
$6.15 / month
$1/1M in · $5/1M out
o4-mini saves approximately $0.13 / month (2%) under this workload.1.0x Savings

o4-mini · Strengths & Key Advantages

  • Cheap reasoning with vision and tool calling
  • Fast enough for interactive agent loops
  • Strong maths performance for its price band
  • Excellent maths accuracy per dollar among o-series models
Considerations & Trade-offs
  • Clearly weaker than o3 on difficult multi-step problems
  • Thinking tokens add latency on hard prompts

Claude Haiku 5.5 · Strengths & Key Advantages

  • Blazing 160 tokens/sec throughput with ultra-low 220ms time-to-first-token
  • Cheap $1.00 / $5.00 API pricing with $0.10 cached inputs
  • Integrated reasoning mode delivering higher accuracy on triage tasks
Considerations & Trade-offs
  • Context window limited to 200K tokens rather than the 1M of Sonnet/Opus
  • Not intended for autonomous multi-file architecture redesigns

Token Use & Task Economics

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

Metrico4-miniClaude Haiku 5.5
Cost per Task
Estimated USD to finish one task
$0.72$0.70
Output Tokens / Task
Tokens generated per task
45K20K
Reasoning Tokens / Task
Thinking tokens burned per task
25K10K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

Featureo4-miniClaude Haiku 5.5
Official API Model ID (SDK)o4-miniclaude-haiku-5-5-20261001
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-042026-10
Knowledge CutoffJune 2024August 2026
ArchitectureCompact reasoning transformerUltra-Fast Lightweight 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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1.1/1M in) across full 200K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.275/1M (no extra cache-write fee)$0.1/1M 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 & 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) · Vision (~258–765 tokens per image tile)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 Modalitiestext, visiontext, vision
Output Modalitiestexttext

o4-mini vs Claude Haiku 5.5: Quick Answers

Which is more intelligent, o4-mini or Claude Haiku 5.5?

Claude Haiku 5.5 is more intelligent. It scores 62 compared with 50 on the composite Intelligence Index.

Which model is faster?

Claude Haiku 5.5 is faster, generating 160 tokens per second compared with 105 tokens per second.

Which model is cheaper to run?

Claude Haiku 5.5 is cheaper at $0.77 per 1M tokens blended, compared with $0.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 5.5 has lower latency, with a time to first token of 0.22s compared with 1.80s.

Verdict

Verdict & Model Selection Recommendation: Choose o4-mini if your priority is Budget reasoning inside agent pipelines and coding assistants. Its performance in demanding tasks justifies its operational token cost. Choose Claude Haiku 5.5 if your workflow prioritizes Real-time user-facing chatbots, rapid text classification, code completion, and edge agent routing. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Frequently asked questions

How does o4-mini compare to Claude Haiku 5.5 in API token pricing and cost per token?+

o4-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens, whereas Claude Haiku 5.5 costs $1.00 input and $5.00 output. Overall, Claude Haiku 5.5 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: o4-mini or Claude Haiku 5.5?+

Both o4-mini and Claude Haiku 5.5 offer an identical context window of 200K tokens (~150k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

Which AI model is better for software engineering and coding: o4-mini or Claude Haiku 5.5?+

o4-mini scores 57.5% on SWE-bench Verified while Claude Haiku 5.5 scores 68.4%. For autonomous software engineering and multi-file debugging, Claude Haiku 5.5 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between o4-mini and Claude Haiku 5.5?+

o4-mini features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Haiku 5.5 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between o4-mini and Claude Haiku 5.5?+

o4-mini generates approximately 105 tokens per second, while Claude Haiku 5.5 delivers 160 tokens per second. In latency-sensitive production environments, Claude Haiku 5.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining o4-mini and Claude Haiku 5.5 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Haiku 5.5 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to o4-mini. This tiered routing pattern cuts overall API bills by up to 70%.

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: GetInfoUs Independent AI Benchmarks & Official API Specs