What are the token costs and operational benchmarks for OpenAI o3-mini?

OpenAI o3-mini (OpenAI) is priced at $1.10 per 1M input tokens and $4.40 per 1M output tokens (with prompt cache reads at $0.550/1M tokens). Built on a Reasoning Transformer architecture with a 204.8k token context window, it delivers 950ms TTFT latency at 98 tokens per sec and scores 49.3% on SWE-bench Verified, 79.7% on GPQA Diamond, 83.2% on MMLU-Pro, and 97.9% on MATH-500 (59.7 IVR).
Verified daily via automated API latency tests and official documentation.
Input / 1M $1.10
Output / 1M $4.40
Cache Read / 1M $0.550
Context Limit 204.8k
TTFT Latency 950ms
Throughput 98 t/s
SWE-bench 49.3%
GPQA Diamond 79.7%

Verified Capability Benchmarks

Composite Intelligence: 73.6/100
SWE-bench Verified
49.3%
GPQA Diamond
79.7%
MMLU-Pro
83.2%
MATH-500
97.9%
HumanEval Coding
92.4%

Architectural & Production Profile

Cost-effective text reasoning model purpose-built for STEM logic, theorem validation, and structured code generation.

Optimal Production Workloads

Competitive math reasoning, automated unit test generation, and structured logic pipelines.

Architecture
Reasoning Transformer
Modalities
Text
Max Output Tokens
100,000 tokens
Blended Rate (3:1)
$1.925 / 1M

Verified Cloud Inference Endpoints Hosting OpenAI o3-mini

Compare latency, streaming speed, and token pricing across cloud API providers.

All Cloud Providers →
Inference Provider Role Input / 1M Output / 1M Avg TTFT Throughput
OpenAI Platform API → Primary Host $1.10 $4.40 950ms 98 tok/s

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

OpenAI o3-mini $42.63

$1.10/1M in · $4.40/1M out

Prompt Cache: $0.550/1M read · $1.10/1M write

Gemini 4 Argon $76.25

$2.00/1M in · $10.00/1M out

Prompt Cache: $0.100/1M read · $0.50/1M write

Projected Monthly Cost Reduction
$33.63 / mo
(44.1% lower cost with OpenAI o3-mini)
Open Full Matchup Analysis →

Head-to-Head Comparisons Involving OpenAI o3-mini (36)

Versus Comparison →

OpenAI o3-mini vs DeepSeek R1

DeepSeek R1 cuts input token costs by 50.0% compared to OpenAI o3-mini ($0.55 vs. $1.10 per 1M input tokens; $2.19 vs. $4.40/1M output). For autonomous software engineering, OpenAI o3-mini leads on SWE-bench Verified (49.3% vs. 49.2%), while OpenAI o3-mini edges ahead on GPQA Diamond scientific reasoning (79.7%). In real-time API production, OpenAI o3-mini achieves a faster 950ms TTFT latency (98.0 tokens/sec).

Versus Comparison →

OpenAI o3-mini vs Gemini 4 Argon

OpenAI o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.8x cost advantage). In terms of operational performance, Gemini 4 Argon delivers lower response latency at 850ms TTFT (100ms faster than OpenAI o3-mini) with 115 vs. 98 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 93.8% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Claude 4.5 Sonnet

OpenAI 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 advantage). In terms of operational performance, Claude 4.5 Sonnet delivers lower response latency at 380ms TTFT (570ms faster than OpenAI o3-mini) with 84 vs. 98 tok/s throughput. Claude 4.5 Sonnet leads coding evaluations at 75.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 84.2% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Claude Opus 5.5

OpenAI o3-mini is 72.5% cheaper for input tokens ($1.10 vs. $4.00 per 1M tokens) and $4.40 vs. $20.00 for output tokens (3.6x cost advantage). In terms of operational performance, Claude Opus 5.5 delivers lower response latency at 680ms TTFT (270ms faster than OpenAI o3-mini) with 95 vs. 98 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 93.2% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemini 3.8 Flash

Gemini 3.8 Flash is 77.3% cheaper for input tokens ($0.25 vs. $1.10 per 1M tokens) and $1.50 vs. $4.40 for output tokens (4.4x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (845ms faster than OpenAI o3-mini) with 210 vs. 98 tok/s throughput. Gemini 3.8 Flash leads coding evaluations at 68.5% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 79.2% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GPT-5

OpenAI 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 advantage). In terms of operational performance, GPT-5 delivers lower response latency at 340ms TTFT (610ms faster than OpenAI o3-mini) with 105 vs. 98 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 85.4% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GPT-6 Astra

OpenAI o3-mini is 89.0% cheaper for input tokens ($1.10 vs. $10.00 per 1M tokens) and $4.40 vs. $50.00 for output tokens (9.1x cost advantage). In terms of operational performance, GPT-6 Astra delivers lower response latency at 740ms TTFT (210ms faster than OpenAI o3-mini) with 74 vs. 98 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 96.0% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs DeepSeek V4 Pro

OpenAI o3-mini is 16.7% cheaper for input tokens ($1.10 vs. $1.32 per 1M tokens) and $4.40 vs. $3.96 for output tokens (1.2x cost advantage). In terms of operational performance, DeepSeek V4 Pro delivers lower response latency at 520ms TTFT (430ms faster than OpenAI o3-mini) with 78 vs. 98 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 90.1% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs DeepSeek V4 Flash Vision (Exp)

DeepSeek V4 Flash Vision (Exp) is 80.0% cheaper for input tokens ($0.22 vs. $1.10 per 1M tokens) and $0.65 vs. $4.40 for output tokens (5.0x cost advantage). In terms of operational performance, DeepSeek V4 Flash Vision (Exp) delivers lower response latency at 310ms TTFT (640ms faster than OpenAI o3-mini) with 165 vs. 98 tok/s throughput. DeepSeek V4 Flash Vision (Exp) leads coding evaluations at 77.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 91.3% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs OpenAI o3

OpenAI 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 advantage). In terms of operational performance, OpenAI o3-mini delivers lower response latency at 950ms TTFT (200ms faster than OpenAI o3) with 98 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 87.7% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Claude 4 Opus

OpenAI o3-mini is 92.7% cheaper for input tokens ($1.10 vs. $15.00 per 1M tokens) and $4.40 vs. $75.00 for output tokens (13.6x cost advantage). In terms of operational performance, Claude 4 Opus delivers lower response latency at 920ms TTFT (30ms faster than OpenAI o3-mini) with 46 vs. 98 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 87.1% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Claude 3.7 Sonnet

OpenAI 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 advantage). In terms of operational performance, Claude 3.7 Sonnet delivers lower response latency at 540ms TTFT (410ms faster than OpenAI o3-mini) with 72 vs. 98 tok/s throughput. Claude 3.7 Sonnet leads coding evaluations at 70.3% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 78.5% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemini 3.1 Pro

OpenAI o3-mini is 12.0% cheaper for input tokens ($1.10 vs. $1.25 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.1x cost advantage). In terms of operational performance, Gemini 3.1 Pro delivers lower response latency at 420ms TTFT (530ms faster than OpenAI o3-mini) with 98 vs. 98 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 82.4% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Grok 4

OpenAI o3-mini is 56.0% cheaper for input tokens ($1.10 vs. $2.50 per 1M tokens) and $4.40 vs. $12.50 for output tokens (2.3x cost advantage). In terms of operational performance, Grok 4 delivers lower response latency at 480ms TTFT (470ms faster than OpenAI o3-mini) with 95 vs. 98 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 86.2% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Llama 4 Maverick

Llama 4 Maverick is 81.8% cheaper for input tokens ($0.20 vs. $1.10 per 1M tokens) and $0.60 vs. $4.40 for output tokens (5.5x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (815ms faster than OpenAI o3-mini) with 175 vs. 98 tok/s throughput. Llama 4 Maverick leads coding evaluations at 62.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 73.8% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Qwen 3.8 Flash Next

Qwen 3.8 Flash Next is 85.5% cheaper for input tokens ($0.16 vs. $1.10 per 1M tokens) and $0.47 vs. $4.40 for output tokens (6.9x cost advantage). In terms of operational performance, Qwen 3.8 Flash Next delivers lower response latency at 280ms TTFT (670ms faster than OpenAI o3-mini) with 185 vs. 98 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 91.7% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is 93.2% cheaper for input tokens ($0.07 vs. $1.10 per 1M tokens) and $0.30 vs. $4.40 for output tokens (14.7x cost advantage). In terms of operational performance, Gemini 3.5 Flash-Lite delivers lower response latency at 78ms TTFT (872ms faster than OpenAI o3-mini) with 265 vs. 98 tok/s throughput. Gemini 3.5 Flash-Lite leads coding evaluations at 55.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 68.4% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs OpenAI o4-mini

OpenAI o3-mini and OpenAI o4-mini share identical input pricing at $1.10 per 1M tokens ($4.40 vs. $4.40 output). In terms of operational performance, OpenAI o4-mini delivers lower response latency at 680ms TTFT (270ms faster than OpenAI o3-mini) with 125 vs. 98 tok/s throughput. OpenAI o4-mini leads coding evaluations at 68.1% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 81.4% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI 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 advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (540ms faster than OpenAI o3-mini) with 78 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 79.7% vs. 59.1% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemma 4 31B IT

Gemma 4 31B IT 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 advantage). In terms of operational performance, Gemma 4 31B IT delivers lower response latency at 115ms TTFT (835ms faster than OpenAI o3-mini) with 155 vs. 98 tok/s throughput. Gemma 4 31B IT leads coding evaluations at 59.2% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 71.2% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI 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 advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (760ms faster than OpenAI o3-mini) with 130 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 79.7% vs. 41.6% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Claude 3.5 Sonnet

OpenAI 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 advantage). In terms of operational performance, Claude 3.5 Sonnet delivers lower response latency at 310ms TTFT (640ms faster than OpenAI o3-mini) with 80 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 49.0% for Claude 3.5 Sonnet and 79.7% vs. 59.4% on GPQA Diamond.

Versus Comparison →

OpenAI 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 advantage). In terms of operational performance, Gemini 2.0 Flash delivers lower response latency at 280ms TTFT (670ms faster than OpenAI o3-mini) with 185 vs. 98 tok/s throughput. Gemini 2.0 Flash leads coding evaluations at 51.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 63.6% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemini 2.5 Flash

Gemini 2.5 Flash is 72.7% cheaper for input tokens ($0.30 vs. $1.10 per 1M tokens) and $2.50 vs. $4.40 for output tokens (3.7x cost advantage). In terms of operational performance, Gemini 2.5 Flash delivers lower response latency at 110ms TTFT (840ms faster than OpenAI o3-mini) with 180 vs. 98 tok/s throughput. Gemini 2.5 Flash leads coding evaluations at 58.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 70.5% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Gemini 2.5 Pro

OpenAI o3-mini is 12.0% cheaper for input tokens ($1.10 vs. $1.25 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.1x cost advantage). In terms of operational performance, Gemini 2.5 Pro delivers lower response latency at 700ms TTFT (250ms faster than OpenAI o3-mini) with 80 vs. 98 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 74.0% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GLM-5.3-Flash

GLM-5.3-Flash is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.40 vs. $4.40 for output tokens (9.2x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (860ms faster than OpenAI o3-mini) with 175 vs. 98 tok/s throughput. GLM-5.3-Flash leads coding evaluations at 52.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 63.5% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GLM-5.3

GLM-5.3 is 68.2% cheaper for input tokens ($0.35 vs. $1.10 per 1M tokens) and $1.00 vs. $4.40 for output tokens (3.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (790ms faster than OpenAI o3-mini) with 120 vs. 98 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 67.0% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GPT-4o Mini

GPT-4o Mini is 86.4% cheaper for input tokens ($0.15 vs. $1.10 per 1M tokens) and $0.60 vs. $4.40 for output tokens (7.3x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (730ms faster than OpenAI o3-mini) with 140 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 79.7% vs. 40.2% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GPT-4o

OpenAI 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 advantage). In terms of operational performance, GPT-4o delivers lower response latency at 280ms TTFT (670ms faster than OpenAI o3-mini) with 100 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 48.0% for GPT-4o and 79.7% vs. 53.6% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs GPT-6.1 Sol

OpenAI o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.8x cost advantage). In terms of operational performance, GPT-6.1 Sol delivers lower response latency at 520ms TTFT (430ms faster than OpenAI o3-mini) with 135 vs. 98 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 92.4% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Grok 3 Mini

Grok 3 Mini is 72.7% cheaper for input tokens ($0.30 vs. $1.10 per 1M tokens) and $1.20 vs. $4.40 for output tokens (3.7x cost advantage). In terms of operational performance, Grok 3 Mini delivers lower response latency at 150ms TTFT (800ms faster than OpenAI o3-mini) with 160 vs. 98 tok/s throughput. Grok 3 Mini leads coding evaluations at 54.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 68.0% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Grok 3

OpenAI 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 advantage). In terms of operational performance, Grok 3 delivers lower response latency at 620ms TTFT (330ms faster than OpenAI o3-mini) with 88 vs. 98 tok/s throughput. Grok 3 leads coding evaluations at 65.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 84.6% vs. 79.7% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Llama 3.3 70B Instruct

Llama 3.3 70B Instruct is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.30 vs. $4.40 for output tokens (9.2x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (805ms faster than OpenAI o3-mini) with 165 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 79.7% vs. 55.6% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Mistral Large 2 (2411)

OpenAI 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 advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (570ms faster than OpenAI o3-mini) with 75 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 79.7% vs. 54.2% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs o1

OpenAI 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 advantage). In terms of operational performance, OpenAI o3-mini delivers lower response latency at 950ms TTFT (1650ms faster than o1) with 98 vs. 48 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 48.9% for o1 and 79.7% vs. 78.0% on GPQA Diamond.

Versus Comparison →

OpenAI o3-mini vs Qwen 3.8 27B

Qwen 3.8 27B is 81.8% cheaper for input tokens ($0.20 vs. $1.10 per 1M tokens) and $0.60 vs. $4.40 for output tokens (5.5x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (830ms faster than OpenAI o3-mini) with 140 vs. 98 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 68.0% vs. 79.7% on GPQA Diamond.

Frequently Asked Questions & Query Fan-Out

How much does OpenAI o3-mini cost per 1M tokens including prompt caching?

OpenAI o3-mini costs $1.10 per million input tokens and $4.40 per million output tokens. Cached input reads cost $0.550 per 1M tokens, reducing repeated context costs by 50%.

What are OpenAI o3-mini's coding and reasoning benchmark scores?

OpenAI o3-mini achieves 49.3% on SWE-bench Verified, 92.4% on HumanEval coding, 79.7% on GPQA Diamond graduate-level science, 83.2% on MMLU-Pro, and 97.9% on MATH-500, earning an overall Inference Value Ratio (IVR) of 59.7/100.

What is the context window, TTFT latency, and token throughput of OpenAI o3-mini?

OpenAI o3-mini supports a 204,800 token context window (100,000 max output tokens) and operates at 950ms average Time to First Token (TTFT) with 98 tokens/sec output streaming throughput.

What are the primary production use cases for OpenAI o3-mini?

Competitive math reasoning, automated unit test generation, and structured logic pipelines.