Claude 3.5 Haiku
Proprietary CommercialDeveloped by Anthropic · Released 2025-01-01
What are the token costs and operational benchmarks for Claude 3.5 Haiku?
Architectural Overview
Frontier foundation model developed by Anthropic featuring Lightweight Dense architecture.
Optimal Production Use Cases
High-speed API routing, conversational triage, extraction, and edge agent tasks.
Interactive Monthly Token Economics & ROI Forecaster
Model your expected production workload across prompt (input) and completion (output) tokens.
Estimated Monthly Spend
$0.8/1M in · $4/1M out
$0.18/1M in · $0.72/1M out
Head-to-Head Comparisons Involving Claude 3.5 Haiku
Claude 3.5 Haiku vs Claude 3.5 Sonnet
Claude 3.5 Haiku is 73.3% cheaper for input tokens ($0.80 vs. $3.00 per 1M tokens) and $4.00 vs. $15.00 for output tokens (3.8x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (180ms faster than Claude 3.5 Sonnet). Claude 3.5 Sonnet leads coding benchmarks at 63.7% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Claude 3.7 Sonnet
Claude 3.5 Haiku is 73.3% cheaper for input tokens ($0.80 vs. $3.00 per 1M tokens) and $4.00 vs. $15.00 for output tokens (3.8x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (510ms faster than Claude 3.7 Sonnet). Claude 3.7 Sonnet leads coding benchmarks at 70.3% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Claude Opus 5
Claude 3.5 Haiku is 84.0% cheaper for input tokens ($0.80 vs. $5.00 per 1M tokens) and $4.00 vs. $25.00 for output tokens (6.2x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (200ms faster than Claude Opus 5). Claude Opus 5 leads coding benchmarks at 82.4% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Codestral 25.01
Codestral 25.01 is 62.5% cheaper for input tokens ($0.30 vs. $0.80 per 1M tokens) and $0.90 vs. $4.00 for output tokens (2.7x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (10ms faster than Codestral 25.01). Codestral 25.01 leads coding benchmarks at 44.2% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Composer 2.5
Claude 3.5 Haiku is 55.6% cheaper for input tokens ($0.80 vs. $1.80 per 1M tokens) and $4.00 vs. $7.20 for output tokens (2.2x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (40ms faster than Composer 2.5). Composer 2.5 leads coding benchmarks at 74.6% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs DeepSeek-R1
DeepSeek-R1 is 31.2% cheaper for input tokens ($0.55 vs. $0.80 per 1M tokens) and $2.19 vs. $4.00 for output tokens (1.5x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (1660ms faster than DeepSeek-R1). DeepSeek-R1 leads coding benchmarks at 49.2% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs DeepSeek-V3
DeepSeek-V3 is 82.5% cheaper for input tokens ($0.14 vs. $0.80 per 1M tokens) and $0.28 vs. $4.00 for output tokens (5.7x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (200ms faster than DeepSeek-V3). DeepSeek-V3 leads coding benchmarks at 42.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs DeepSeek-V4 Flash
DeepSeek-V4 Flash is 82.5% cheaper for input tokens ($0.14 vs. $0.80 per 1M tokens) and $0.56 vs. $4.00 for output tokens (5.7x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (10ms faster than DeepSeek-V4 Flash). DeepSeek-V4 Flash leads coding benchmarks at 62.4% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Fable 5
Claude 3.5 Haiku is 60.0% cheaper for input tokens ($0.80 vs. $2.00 per 1M tokens) and $4.00 vs. $8.00 for output tokens (2.5x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (100ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Gemini 2.0 Flash
Gemini 2.0 Flash is 87.5% cheaper for input tokens ($0.10 vs. $0.80 per 1M tokens) and $0.40 vs. $4.00 for output tokens (8.0x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (240ms faster than Gemini 2.0 Flash). Gemini 2.0 Flash leads coding benchmarks at 48.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Gemini 3.7 Flash
Gemini 3.7 Flash is 90.0% cheaper for input tokens ($0.08 vs. $0.80 per 1M tokens) and $0.32 vs. $4.00 for output tokens (10.0x cost difference). In terms of operational performance, Gemini 3.7 Flash delivers faster response latency with 75ms TTFT (65ms faster than Claude 3.5 Haiku). Gemini 3.7 Flash leads coding benchmarks at 68.2% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs GLM 5.3 Flash
GLM 5.3 Flash is 81.2% cheaper for input tokens ($0.15 vs. $0.80 per 1M tokens) and $0.50 vs. $4.00 for output tokens (5.3x cost difference). In terms of operational performance, GLM 5.3 Flash delivers faster response latency with 130ms TTFT (10ms faster than Claude 3.5 Haiku). GLM 5.3 Flash leads coding benchmarks at 54.2% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs OpenAI GPT-4o
Claude 3.5 Haiku is 68.0% cheaper for input tokens ($0.80 vs. $2.50 per 1M tokens) and $4.00 vs. $10.00 for output tokens (3.1x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (140ms faster than OpenAI GPT-4o). Claude 3.5 Haiku leads coding benchmarks at 40.6% SWE-bench vs. 38.8% for OpenAI GPT-4o.
Claude 3.5 Haiku vs GPT-5.6 Luna
GPT-5.6 Luna is 77.5% cheaper for input tokens ($0.18 vs. $0.80 per 1M tokens) and $0.72 vs. $4.00 for output tokens (4.4x cost difference). In terms of operational performance, GPT-5.6 Luna delivers faster response latency with 90ms TTFT (50ms faster than Claude 3.5 Haiku). GPT-5.6 Luna leads coding benchmarks at 48.5% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs GPT-5.6 Sol
Claude 3.5 Haiku is 90.0% cheaper for input tokens ($0.80 vs. $8.00 per 1M tokens) and $4.00 vs. $32.00 for output tokens (10.0x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (280ms faster than GPT-5.6 Sol). GPT-5.6 Sol leads coding benchmarks at 79.5% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs GPT-5.6 Terra
Claude 3.5 Haiku is 46.7% cheaper for input tokens ($0.80 vs. $1.50 per 1M tokens) and $4.00 vs. $6.00 for output tokens (1.9x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (70ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Grok 3
Claude 3.5 Haiku is 73.3% cheaper for input tokens ($0.80 vs. $3.00 per 1M tokens) and $4.00 vs. $15.00 for output tokens (3.8x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (710ms faster than Grok 3). Grok 3 leads coding benchmarks at 58.5% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs xAI Grok 4.6
Claude 3.5 Haiku is 60.0% cheaper for input tokens ($0.80 vs. $2.00 per 1M tokens) and $4.00 vs. $6.00 for output tokens (2.5x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (140ms faster than xAI Grok 4.6). xAI Grok 4.6 leads coding benchmarks at 76.8% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is 77.5% cheaper for input tokens ($0.18 vs. $0.80 per 1M tokens) and $0.40 vs. $4.00 for output tokens (4.4x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (280ms faster than Llama 3.3 70B Instruct). Claude 3.5 Haiku leads coding benchmarks at 40.6% SWE-bench vs. 38.8% for Llama 3.3 70B Instruct.
Claude 3.5 Haiku vs Mistral Large 2
Claude 3.5 Haiku is 60.0% cheaper for input tokens ($0.80 vs. $2.00 per 1M tokens) and $4.00 vs. $6.00 for output tokens (2.5x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (410ms faster than Mistral Large 2). Claude 3.5 Haiku leads coding benchmarks at 40.6% SWE-bench vs. 39.0% for Mistral Large 2.
Claude 3.5 Haiku vs OpenAI o1
Claude 3.5 Haiku is 94.7% cheaper for input tokens ($0.80 vs. $15.00 per 1M tokens) and $4.00 vs. $60.00 for output tokens (18.8x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (710ms faster than OpenAI o1). OpenAI o1 leads coding benchmarks at 48.9% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs o3-mini
Claude 3.5 Haiku is 27.3% cheaper for input tokens ($0.80 vs. $1.10 per 1M tokens) and $4.00 vs. $4.40 for output tokens (1.4x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (1060ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Microsoft Phi-4 (14B)
Microsoft Phi-4 (14B) is 85.0% cheaper for input tokens ($0.12 vs. $0.80 per 1M tokens) and $0.36 vs. $4.00 for output tokens (6.7x cost difference). In terms of operational performance, Microsoft Phi-4 (14B) delivers faster response latency with 110ms TTFT (30ms faster than Claude 3.5 Haiku). Microsoft Phi-4 (14B) leads coding benchmarks at 42.1% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Qwen 2.5 72B Instruct
Qwen 2.5 72B Instruct is 56.2% cheaper for input tokens ($0.35 vs. $0.80 per 1M tokens) and $0.40 vs. $4.00 for output tokens (2.3x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (280ms faster than Qwen 2.5 72B Instruct). Qwen 2.5 72B Instruct leads coding benchmarks at 44.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Qwen 2.5 Max
Qwen 2.5 Max is 65.0% cheaper for input tokens ($0.28 vs. $0.80 per 1M tokens) and $0.84 vs. $4.00 for output tokens (2.9x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (340ms faster than Qwen 2.5 Max). Qwen 2.5 Max leads coding benchmarks at 44.2% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Claude 3.5 Haiku vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 85.0% cheaper for input tokens ($0.12 vs. $0.80 per 1M tokens) and $0.48 vs. $4.00 for output tokens (6.7x cost difference). In terms of operational performance, Qwen 3.8 Flash Next delivers faster response latency with 120ms TTFT (20ms faster than Claude 3.5 Haiku). Qwen 3.8 Flash Next leads coding benchmarks at 56.8% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
Frequently Asked Questions & Query Fan-Out
How much does Claude 3.5 Haiku cost per 1M tokens?
Claude 3.5 Haiku costs $0.80 per million prompt (input) tokens and $4.00 per million completion (output) tokens.
What is the context window for Claude 3.5 Haiku?
Claude 3.5 Haiku supports a maximum context window of 204,800 tokens, with a maximum single-generation output of 8,192 tokens.
What are the primary use cases for Claude 3.5 Haiku?
High-speed API routing, conversational triage, extraction, and edge agent tasks.