What are the token costs and operational benchmarks for GPT-4.5?

GPT-4.5 is priced at $75.00 per million input tokens and $150.00 per million output tokens. It features a 131.072k token context window, an average response latency of 850ms TTFT, and achieves 38% on SWE-bench Verified and 84% on MMLU-Pro.
Verified daily via automated API latency tests and official documentation.
Input / 1M $75.00
Output / 1M $150.00
Context Limit 131.072k
TTFT Latency 850ms
SWE-bench 38%
Throughput 45 t/s

Architectural Overview

Frontier foundation model developed by OpenAI featuring Dense Large-Scale Transformer architecture.

Optimal Production Use Cases

Deep world-knowledge synthesis, high-EQ conversational nuance, and long-form creative generation requiring massive pretraining breadth.

Interactive Monthly Token Economics & ROI Forecaster

Model your expected production workload across prompt (input) and completion (output) tokens with prompt caching economics.

Live Calculation Engine
10.0M Tokens
100K 50M 250M 500M+
2.5M Tokens
100K 10M 50M 100M+

Estimated Monthly Spend

GPT-4.5 $1,125.00

$75.00/1M in · $150.00/1M out

Prompt Cache: $37.500/1M read · $75.00/1M write

Qwen 3.8 Flash Next $1.88

$0.10/1M in · $0.35/1M out

Prompt Cache: $0.020/1M read · $0.10/1M write

Projected Monthly Cost Reduction
$1,123.13 / mo
(99.8% lower cost with Qwen 3.8 Flash Next)

Head-to-Head Comparisons Involving GPT-4.5

Versus Comparison →

GPT-4.5 vs Claude 3.5 Haiku

**Claude 3.5 Haiku provides unmatched cost efficiency and speed over GPT-4.5 while leading coding benchmarks.** At $0.80 input and $4.00 output per 1M tokens, Haiku is 98.9% cheaper than GPT-4.5 ($75.00/$150.00). Additionally, Haiku delivers a rapid 190ms TTFT (660ms faster) and outperforms GPT-4.5 on SWE-bench (40.6% vs. 38.0%).

Versus Comparison →

GPT-4.5 vs Claude 3.5 Sonnet

**Claude 3.5 Sonnet decisively outperforms GPT-4.5 across cost efficiency, speed, and coding performance.** Claude is 96.0% cheaper on inputs at $3.00 versus $75.00 per 1M tokens, alongside $15.00 versus $150.00 for outputs. It responds faster with a 310ms TTFT (540ms lower latency) while leading benchmarks at 49.0% SWE-bench versus GPT-4.5's 38.0%.

Versus Comparison →

GPT-4.5 vs Claude 3.7 Sonnet

**Claude 3.7 Sonnet dramatically outperforms GPT-4.5 across cost, latency, and coding benchmarks.** It is 96.0% cheaper for inputs at $3.00 versus $75.00 per 1M tokens, with outputs at $15.00 versus $150.00. Claude also scores 70.3% on SWE-

Versus Comparison →

GPT-4.5 vs DeepSeek R1

**DeepSeek-R1 delivers disruptive cost efficiency and superior coding performance over GPT-4.5.** DeepSeek-R1 is 99.3% cheaper for inputs ($0.55 vs. $75.00 per 1M) and leads SWE-bench at 52.0% versus 38.0%. However, GPT-4.5 commands lower latency with an 850ms TTFT, responding 250ms faster than DeepSeek-R1 for speed-critical deployments.

Versus Comparison →

GPT-4.5 vs DeepSeek V3

**DeepSeek V3 provides unmatched cost efficiency, operating 99.8% cheaper than GPT-4.5 while outperforming it in speed and coding.** It costs just $0.14/$0.28 per 1M input/output tokens versus GPT-4.5’s $75.00/$150.00 (a 535.7x reduction). Furthermore, DeepSeek V3 achieves a 410ms TTFT (440ms faster) and leads coding at 42.0% vs. 38.0% on SWE-bench.

Versus Comparison →

GPT-4.5 vs DeepSeek-V4 Flash Vision Exp

**DeepSeek-V4 Flash Vision Exp decisively outperforms GPT-4.5 at a fraction of the cost.** It is 99.8% cheaper ($0.14 input, $0.56 output vs. $75.00 and $150.00 per 1M tokens), while responding with a 140ms TTFT (710ms faster). Furthermore, DeepSeek dominates coding benchmarks, scoring 64.2% on SWE-bench compared to GPT-4.5’s 38.0%.

Versus Comparison →

GPT-4.5 vs Gemini 2.0 Flash

**Gemini 2.0 Flash delivers overwhelming cost efficiency and speed advantages over GPT-4.5 while leading in core benchmarks.** It is 99.9% cheaper at $0.10 per 1M input tokens versus $75.00, and $0.40 versus $150.00 for outputs. Flash also achieves a 220ms TTFT (630ms faster) and superior 45.2% SWE-bench coding accuracy versus GPT-4.5's 38.0%.

Versus Comparison →

GPT-4.5 vs Gemini 2.5 Flash

**Gemini 2.5 Flash delivers a massive price-performance advantage over GPT-4.5.** It is 99.6% cheaper for input tokens at $0.30 versus $75.00 per 1M tokens ($2.50 vs. $150.00 output). Additionally, Gemini 2.5 Flash is 740ms faster with a 110ms TTFT and leads coding benchmarks with 58.0% on SWE-bench compared to GPT-4.5's 38.0%.

Versus Comparison →

GPT-4.5 vs Gemini 2.5 Pro

**Gemini 2.5 Pro drastically outperforms GPT-4.5 on cost-efficiency and coding capabilities.** It is 98.3% cheaper for input ($1.25 vs. $75.00/1M tokens) and 60.0x cheaper for output ($10.00 vs. $150.00/1M tokens). Gemini also leads in speed with a 700ms TTFT (150ms faster) and dominates coding at 63.8% versus 38.0% on SWE-bench.

Versus Comparison →

GPT-4.5 vs GLM-5.3-Flash

**GLM-5.3-Flash decisively outperforms GPT-4.5 across pricing, speed, and coding capabilities.** It is 99.8% cheaper, costing $0.12 versus $75.00 for input and $0.40 versus $150.00 for output per million tokens. Additionally, GLM-5.3-Flash delivers an ultra-fast 90ms TTFT (760ms faster) and leads coding with 52.8% on SWE-bench versus 38.0% for GPT-4.5.

Versus Comparison →

GPT-4.5 vs GLM-5.3

**GLM-5.3 decisively outperforms GPT-4.5 across efficiency and software engineering capabilities at a fraction of the cost.** It is 99.5% cheaper, charging $0.35 input and $1.00 output per 1M tokens versus $75.00 and $150.00. Furthermore, GLM-5.3 delivers a 160ms TTFT (690ms faster) and leads coding benchmarks with 56.0% on SWE-bench compared to GPT-4.5's 38.0%.

Versus Comparison →

GPT-4.5 vs GPT-4o

**GPT-4o dominates overall efficiency, delivering vastly superior economics and speed over GPT-4.5.** It is 96.7% cheaper for input tokens ($2.50 vs. $75.00 per 1M) and $10.00 vs. $150.00 for outputs. GPT-4o also achieves lower latency with a 280ms TTFT (570ms faster) and outperforms GPT-4.5 in coding (48.0% vs. 38.0% SWE-bench).

Versus Comparison →

GPT-4.5 vs GPT-4o Mini

**GPT-4o Mini delivers an overwhelming cost and efficiency advantage over GPT-4.5.** It is 99.8% cheaper, costing $0.15 versus $75.00 for input and $0.60 versus $150.00 for output per 1M tokens. GPT-4o Mini also responds faster with a 220ms TTFT (630ms faster) and leads coding capabilities at 41.0% versus 38.0% on SWE-bench.

Versus Comparison →

GPT-4.5 vs Grok 3

**Grok 3 delivers vastly superior economics and coding capability compared to GPT-4.5.** Grok 3 slashes input costs by 96.0% ($3.00 vs. $75.00 per 1M) and output costs ($15.00 vs. $150.00 per 1M). It responds faster with a 750ms TTFT (100ms lead) and decisively outperforms GPT-4.5 on SWE-bench (58.0% vs. 38.0%).

Versus Comparison →

GPT-4.5 vs Grok 3 Mini

**Grok 3 Mini delivers massive cost disruption while beating GPT-4.5 in performance and speed.** Priced at $0.30 input and $1.20 output per 1M tokens, Grok 3 Mini is 99.6% cheaper (a 250.0x cost difference). It also achieves superior coding results at 54.0% SWE-bench versus 38.0%, with a 150ms TTFT that is 700ms faster.

Versus Comparison →

GPT-4.5 vs Llama 3.3 70B Instruct

**Llama 3.3 70B Instruct delivers vastly superior cost efficiency and performance over GPT-4.5.** It is 99.8% cheaper, priced at $0.12 versus $75.00 for input and $0.30 versus $150.00 for output per 1M tokens. Llama also provides a faster 450ms TTFT (400ms advantage) and leads SWE-bench coding benchmarks at 42.5% against GPT-4.5's 38.0%.

Versus Comparison →

GPT-4.5 vs Mistral Large 2

**Mistral Large 2 delivers vastly superior cost efficiency and faster execution than GPT-4.5.** It is 97.3% cheaper at $2.00 input and $6.00 output per 1M tokens versus $75.00 and $150.00 (a 37.5x cost difference). Mistral Large 2 also achieves a 520ms TTFT (330ms faster

Versus Comparison →

GPT-4.5 vs Mistral Large 2 (2411)

**Mistral Large 2411 delivers overwhelming cost efficiency with nearly identical capability compared to GPT-4.5.** It is 97.3% cheaper at $2.00 versus $75.00 input and $6.00 versus $150.00 output per 1M tokens. Mistral also lowers latency to a 360ms TTFT (490ms faster), while GPT-4.5 holds a slim 38.0% versus 37.8% SWE-bench lead.

Versus Comparison →

GPT-4.5 vs o1

**o1 delivers superior technical reasoning at substantially lower compute costs, whereas GPT-4.5 provides superior interactive latency.** o1 is 80.0% cheaper on inputs ($15.00 vs. $75.00 per 1M) and leads SWE-bench at 48.9% versus 38.0%. However, GPT-4.5 delivers faster performance with an 850ms TTFT, beating o1 by 1750ms.

Versus Comparison →

GPT-4.5 vs OpenAI o3-mini

**OpenAI o3-mini delivers vastly superior cost efficiency and coding performance over GPT-4.5.** Costing $1.10 per 1M input tokens versus $75.00, o3-mini is 98.5% cheaper and leads SWE-bench at 49.3% versus 38.0%. For output, o3-mini costs $4.40 versus $150

Versus Comparison →

GPT-4.5 vs Qwen 3.8 27B

**Qwen 3.8 27B delivers vastly superior value, slashing costs by 99.7% while outperforming GPT-4.5 in key capabilities.** At $0.20 input and $0.60 output per 1M tokens, Qwen is up to 375x cheaper than GPT-4.5 ($75.00/$150.00). It also responds 730ms faster with a 120ms TTFT and dominates SWE-bench coding at 58.4% versus 38.0%.

Versus Comparison →

GPT-4.5 vs Qwen 3.8 Flash Next

**Qwen 3.8 Flash Next completely outclasses GPT-4.5 across cost, latency, and coding benchmarks.** Qwen is 99.9% cheaper at $0.10 input and $0.35 output per 1M tokens versus $75.00 and $150.00 for GPT-4.5. Furthermore, Qwen scores 61.0% on SWE-bench compared to GPT-4.5's 38.0%, while delivering a 95ms TTFT, running 755ms faster.

Frequently Asked Questions & Query Fan-Out

How much does GPT-4.5 cost per 1M tokens?

GPT-4.5 costs $75.00 per million prompt (input) tokens and $150.00 per million completion (output) tokens.

What is the context window for GPT-4.5?

GPT-4.5 supports a maximum context window of 131,072 tokens, with a maximum single-generation output of 16,384 tokens.

What are the primary use cases for GPT-4.5?

Deep world-knowledge synthesis, high-EQ conversational nuance, and long-form creative generation requiring massive pretraining breadth.