o3-mini
Proprietary CommercialDeveloped by OpenAI · Released 2025-01-01
What are the token costs and operational benchmarks for o3-mini?
Architectural Overview
Frontier foundation model developed by OpenAI featuring Reasoning MoE architecture.
Optimal Production Use Cases
Cost-efficient STEM reasoning, high-throughput math problem-solving, and structured code synthesis.
Interactive Monthly Token Economics & ROI Forecaster
Model your expected production workload across prompt (input) and completion (output) tokens.
Estimated Monthly Spend
$1.1/1M in · $4.4/1M out
$0.18/1M in · $0.72/1M out
Head-to-Head Comparisons Involving o3-mini
o3-mini vs Claude 3.5 Haiku
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.
o3-mini vs Claude 3.5 Sonnet
o3-mini is 63.3% cheaper for input tokens ($1.10 vs. $3.00 per 1M tokens) and $4.40 vs. $15.00 for output tokens (2.7x cost difference). In terms of operational performance, Claude 3.5 Sonnet delivers faster response latency with 320ms TTFT (880ms faster than o3-mini). Claude 3.5 Sonnet leads coding benchmarks at 63.7% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Claude 3.7 Sonnet
o3-mini is 63.3% cheaper for input tokens ($1.10 vs. $3.00 per 1M tokens) and $4.40 vs. $15.00 for output tokens (2.7x cost difference). In terms of operational performance, Claude 3.7 Sonnet delivers faster response latency with 650ms TTFT (550ms faster than o3-mini). Claude 3.7 Sonnet leads coding benchmarks at 70.3% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Claude Opus 5
o3-mini is 78.0% cheaper for input tokens ($1.10 vs. $5.00 per 1M tokens) and $4.40 vs. $25.00 for output tokens (4.5x cost difference). In terms of operational performance, Claude Opus 5 delivers faster response latency with 340ms TTFT (860ms faster than o3-mini). Claude Opus 5 leads coding benchmarks at 82.4% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Codestral 25.01
Codestral 25.01 is 72.7% cheaper for input tokens ($0.30 vs. $1.10 per 1M tokens) and $0.90 vs. $4.40 for output tokens (3.7x cost difference). In terms of operational performance, Codestral 25.01 delivers faster response latency with 150ms TTFT (1050ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 44.2% for Codestral 25.01.
o3-mini vs Composer 2.5
o3-mini is 38.9% cheaper for input tokens ($1.10 vs. $1.80 per 1M tokens) and $4.40 vs. $7.20 for output tokens (1.6x cost difference). In terms of operational performance, Composer 2.5 delivers faster response latency with 180ms TTFT (1020ms faster than o3-mini). Composer 2.5 leads coding benchmarks at 74.6% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs DeepSeek-R1
DeepSeek-R1 is 50.0% cheaper for input tokens ($0.55 vs. $1.10 per 1M tokens) and $2.19 vs. $4.40 for output tokens (2.0x cost difference). In terms of operational performance, o3-mini delivers faster response latency with 1200ms TTFT (600ms faster than DeepSeek-R1). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 49.2% for DeepSeek-R1.
o3-mini vs DeepSeek-V3
DeepSeek-V3 is 87.3% cheaper for input tokens ($0.14 vs. $1.10 per 1M tokens) and $0.28 vs. $4.40 for output tokens (7.9x cost difference). In terms of operational performance, DeepSeek-V3 delivers faster response latency with 340ms TTFT (860ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 42.0% for DeepSeek-V3.
o3-mini vs DeepSeek-V4 Flash
DeepSeek-V4 Flash is 87.3% cheaper for input tokens ($0.14 vs. $1.10 per 1M tokens) and $0.56 vs. $4.40 for output tokens (7.9x cost difference). In terms of operational performance, DeepSeek-V4 Flash delivers faster response latency with 150ms TTFT (1050ms faster than o3-mini). DeepSeek-V4 Flash leads coding benchmarks at 62.4% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Fable 5
o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $8.00 for output tokens (1.8x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (960ms faster than o3-mini). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Gemini 2.0 Flash
Gemini 2.0 Flash is 90.9% cheaper for input tokens ($0.10 vs. $1.10 per 1M tokens) and $0.40 vs. $4.40 for output tokens (11.0x cost difference). In terms of operational performance, Gemini 2.0 Flash delivers faster response latency with 380ms TTFT (820ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 48.0% for Gemini 2.0 Flash.
o3-mini vs Gemini 3.7 Flash
Gemini 3.7 Flash is 92.7% cheaper for input tokens ($0.08 vs. $1.10 per 1M tokens) and $0.32 vs. $4.40 for output tokens (13.8x cost difference). In terms of operational performance, Gemini 3.7 Flash delivers faster response latency with 75ms TTFT (1125ms faster than o3-mini). Gemini 3.7 Flash leads coding benchmarks at 68.2% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs GLM 5.3 Flash
GLM 5.3 Flash is 86.4% cheaper for input tokens ($0.15 vs. $1.10 per 1M tokens) and $0.50 vs. $4.40 for output tokens (7.3x cost difference). In terms of operational performance, GLM 5.3 Flash delivers faster response latency with 130ms TTFT (1070ms faster than o3-mini). GLM 5.3 Flash leads coding benchmarks at 54.2% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs OpenAI GPT-4o
o3-mini is 56.0% cheaper for input tokens ($1.10 vs. $2.50 per 1M tokens) and $4.40 vs. $10.00 for output tokens (2.3x cost difference). In terms of operational performance, OpenAI GPT-4o delivers faster response latency with 280ms TTFT (920ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 38.8% for OpenAI GPT-4o.
o3-mini vs GPT-5.6 Luna
GPT-5.6 Luna is 83.6% cheaper for input tokens ($0.18 vs. $1.10 per 1M tokens) and $0.72 vs. $4.40 for output tokens (6.1x cost difference). In terms of operational performance, GPT-5.6 Luna delivers faster response latency with 90ms TTFT (1110ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 48.5% for GPT-5.6 Luna.
o3-mini vs GPT-5.6 Sol
o3-mini is 86.2% cheaper for input tokens ($1.10 vs. $8.00 per 1M tokens) and $4.40 vs. $32.00 for output tokens (7.3x cost difference). In terms of operational performance, GPT-5.6 Sol delivers faster response latency with 420ms TTFT (780ms faster than o3-mini). GPT-5.6 Sol leads coding benchmarks at 79.5% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs GPT-5.6 Terra
o3-mini is 26.7% cheaper for input tokens ($1.10 vs. $1.50 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.4x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (990ms faster than o3-mini). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Grok 3
o3-mini is 63.3% cheaper for input tokens ($1.10 vs. $3.00 per 1M tokens) and $4.40 vs. $15.00 for output tokens (2.7x cost difference). In terms of operational performance, Grok 3 delivers faster response latency with 850ms TTFT (350ms faster than o3-mini). Grok 3 leads coding benchmarks at 58.5% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs xAI Grok 4.6
o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.8x cost difference). In terms of operational performance, xAI Grok 4.6 delivers faster response latency with 280ms TTFT (920ms faster than o3-mini). xAI Grok 4.6 leads coding benchmarks at 76.8% SWE-bench vs. 49.3% for o3-mini.
o3-mini vs Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is 83.6% cheaper for input tokens ($0.18 vs. $1.10 per 1M tokens) and $0.40 vs. $4.40 for output tokens (6.1x cost difference). In terms of operational performance, Llama 3.3 70B Instruct delivers faster response latency with 420ms TTFT (780ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 38.8% for Llama 3.3 70B Instruct.
o3-mini vs Mistral Large 2
o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.8x cost difference). In terms of operational performance, Mistral Large 2 delivers faster response latency with 550ms TTFT (650ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 39.0% for Mistral Large 2.
o3-mini vs OpenAI o1
o3-mini is 92.7% cheaper for input tokens ($1.10 vs. $15.00 per 1M tokens) and $4.40 vs. $60.00 for output tokens (13.6x cost difference). In terms of operational performance, OpenAI o1 delivers faster response latency with 850ms TTFT (350ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 48.9% for OpenAI o1.
o3-mini vs Microsoft Phi-4 (14B)
Microsoft Phi-4 (14B) is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.36 vs. $4.40 for output tokens (9.2x cost difference). In terms of operational performance, Microsoft Phi-4 (14B) delivers faster response latency with 110ms TTFT (1090ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 42.1% for Microsoft Phi-4 (14B).
o3-mini vs Qwen 2.5 72B Instruct
Qwen 2.5 72B Instruct is 68.2% cheaper for input tokens ($0.35 vs. $1.10 per 1M tokens) and $0.40 vs. $4.40 for output tokens (3.1x cost difference). In terms of operational performance, Qwen 2.5 72B Instruct delivers faster response latency with 420ms TTFT (780ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 44.0% for Qwen 2.5 72B Instruct.
o3-mini vs Qwen 2.5 Max
Qwen 2.5 Max is 74.5% cheaper for input tokens ($0.28 vs. $1.10 per 1M tokens) and $0.84 vs. $4.40 for output tokens (3.9x cost difference). In terms of operational performance, Qwen 2.5 Max delivers faster response latency with 480ms TTFT (720ms faster than o3-mini). o3-mini leads coding benchmarks at 49.3% SWE-bench vs. 44.2% for Qwen 2.5 Max.
o3-mini vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.48 vs. $4.40 for output tokens (9.2x cost difference). In terms of operational performance, Qwen 3.8 Flash Next delivers faster response latency with 120ms TTFT (1080ms faster than o3-mini). Qwen 3.8 Flash Next leads coding benchmarks at 56.8% SWE-bench vs. 49.3% for o3-mini.
Frequently Asked Questions & Query Fan-Out
How much does o3-mini cost per 1M tokens?
o3-mini costs $1.10 per million prompt (input) tokens and $4.40 per million completion (output) tokens.
What is the context window for o3-mini?
o3-mini supports a maximum context window of 204,800 tokens, with a maximum single-generation output of 100,000 tokens.
What are the primary use cases for o3-mini?
Cost-efficient STEM reasoning, high-throughput math problem-solving, and structured code synthesis.