GPT-4o vs GPT-5.2
GPT-4o (May 2024) and GPT-5.2 (December 2025) sit 19 months apart, and it shows. GPT-5.2 triples the context window, adds a reasoning-effort parameter (none through xhigh), and posts higher Design Arena scores in every overlapping category. GPT-4o still has a place: it's simpler, has no reasoning overhead, and its completion price is lower. This comparison covers where each model actually wins.
Spec vs spec
| Spec | GPT-4o | GPT-5.2 |
|---|---|---|
| Context window | 128K | 400K |
| Max output | 16K | 128K |
| Input modalities | text, image, file | file, image, text |
| Output modalities | text | text |
| Knowledge cutoff | Oct 31, 2023 | — |
| Released | May 13, 2024 | Dec 10, 2025 |
| Reasoning | — | optional |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
openai/gpt-4o
Input · 1M tokens
$2.50 + 3%$2.58
Output · 1M tokens
$10.00 + 3%$10.30
FEE — FLAT, EVERY MODEL3%
openai/gpt-5.2
Input · 1M tokens
$1.75 + 3%$1.80
Output · 1M tokens
$14.00 + 3%$14.42
Cache read · 1M tokens
$0.175 + 3%$0.180
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
openai/gpt-4oCheaper
$46.35
$45.00 provider + 3%
openai/gpt-5.2
$46.87
$45.50 provider + 3%
Benchmarks
Design Arena categories where both models have results. Higher Elo and lower rank win.
| GPT-4o | GPT-5.2 | |||
|---|---|---|---|---|
| Category | Elo | Rank | Elo | Rank |
| 3D | 945 | #92 | 1156 | #60 |
| Code | 910 | #104 | 1219 | #42 |
| Data viz | 901 | #101 | 1245 | #31 |
| Game dev | 972 | #98 | 1260 | #29 |
| UI components | 942 | #96 | 1243 | #32 |
| Websites | 874 | #109 | 1237 | #34 |
Head-to-head preference voting. How we filter and rank
Pricing math
On OpenKey, GPT-4o costs $2.575/M input and $10.30/M output (provider price $2.50 / $10.00 x 1.03). GPT-5.2 costs $1.8025/M input and $14.42/M output (provider price $1.75 / $14.00 x 1.03) — cheaper on input, pricier on output, and it also supports cache reads at $0.175/M provider-side that GPT-4o doesn't offer at all.
For a workload of 10M input tokens and 2M output tokens: GPT-4o runs $45.00 total, GPT-5.2 runs $45.50. Nearly identical at this ratio — GPT-5.2's cheaper input offsets its pricier output almost exactly. If your workload skews output-heavy, GPT-4o pulls ahead; if it's input-heavy (e.g., long documents, RAG), GPT-5.2's lower per-token input cost and cache pricing start to matter more than this snapshot shows.
Coding and agent benchmarks
GPT-5.2 was scored across both the models arena and a dedicated agents arena on Design Arena; GPT-4o was only measured in the models arena. Where they overlap: codecategories elo 1219 vs 910 (rank 42 vs 104), gamedev 1260 vs 972 (rank 29 vs 98), dataviz 1245 vs 901 (rank 31 vs 101), uicomponent 1243 vs 942 (rank 32 vs 96), 3d 1156 vs 945 (rank 60 vs 92), website 1237 vs 874 (rank 34 vs 109). GPT-5.2 also has scores in fullstack (1110, rank 21), webapps (1156, rank 19), mobileapps (1173, rank 23), androidnative (1074, rank 22), and godotgamedev (1183, rank 13) — categories GPT-4o has no data for. If you're evaluating a model for a coding agent, GPT-4o isn't in the same tier.
Context and long-document work
GPT-5.2 handles 400,000 tokens of context against GPT-4o's 128,000 — a 3.1x jump (context ratio 0.32 when comparing 4o to 5.2). Max output tokens tell the same story: GPT-5.2 allows 128,000 tokens out versus GPT-4o's 16,384, an 8x difference. For summarizing large codebases, long legal documents, or multi-file diffs in one pass, GPT-4o will truncate or force chunking where GPT-5.2 won't. GPT-5.2 also lacks a published knowledge cutoff in this data, while GPT-4o's is 2023-10-31 — worth checking directly if recency matters for your use case.
Reasoning and parameter support
GPT-5.2 exposes a `reasoning` parameter with five effort levels — none, low, medium, high, xhigh — defaulting to medium, plus `include_reasoning` to surface the trace. GPT-4o has no reasoning parameter at all; it's a single-pass model. GPT-4o instead supports a wider standard toolkit: `logit_bias`, `logprobs`, `top_logprobs`, `frequency_penalty`, `presence_penalty`, and `web_search_options`, none of which appear in GPT-5.2's supported parameter list. If your pipeline depends on logprobs or penalty tuning, GPT-4o is the only one of the two that supports it.
When to pick each
Pick GPT-5.2 for coding agents, long-context tasks (>128K tokens), anything needing adjustable reasoning depth, or work where input tokens dominate the bill. Pick GPT-4o when you need `logprobs` or `logit_bias` for classification/scoring pipelines, when output-heavy workloads make its lower completion price relevant, or when you don't need agentic capability and want a simpler single-pass model. Both are available on OpenKey with one API key and a flat 3% fee over provider list price, so switching between them mid-project doesn't require separate billing or credentials.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| Coding agent / autonomous dev tasks | GPT-5.2 | Scores in dedicated agents arena categories (fullstack rank 21, webapps rank 19) that GPT-4o has no data for at all. |
| Long document / large codebase analysis | GPT-5.2 | 400K context vs 128K — a 3.1x larger window in a single pass. |
| Classification pipelines needing logprobs | GPT-4o | Supports `logprobs` and `top_logprobs`; GPT-5.2's parameter list omits both. |
| Output-heavy generation (long completions, cheap per-token) | GPT-4o | $10.30/M output on OpenKey vs GPT-5.2's $14.42/M. |
| UI component or website generation | GPT-5.2 | Website category elo 1237 (rank 34) vs GPT-4o's 874 (rank 109). |
| Variable reasoning depth per request | GPT-5.2 | Only model with a `reasoning` parameter (none through xhigh); GPT-4o has none. |
Questions
- Is GPT-5.2 more expensive than GPT-4o?
- It depends on the mix. For 10M input + 2M output tokens, GPT-4o costs $45.00 on OpenKey and GPT-5.2 costs $45.50 — nearly the same. GPT-5.2's input price ($1.8025/M) is lower than GPT-4o's ($2.575/M), but its output price ($14.42/M) is higher than GPT-4o's ($10.30/M).
- How much bigger is GPT-5.2's context window?
- GPT-5.2 supports 400,000 tokens of context versus GPT-4o's 128,000 — roughly 3.1x more. Max output tokens jump even more: 128,000 for GPT-5.2 against 16,384 for GPT-4o, an 8x difference.
- Does GPT-4o support reasoning effort levels like GPT-5.2?
- No. GPT-4o has no `reasoning` parameter and no reasoning field in its spec. GPT-5.2 supports five effort levels — none, low, medium, high, xhigh — with medium as the default.
- Which model scores higher on coding benchmarks?
- GPT-5.2, across every shared Design Arena category. In codecategories it scores elo 1219 (rank 42) versus GPT-4o's 910 (rank 104). GPT-5.2 also has separate agents-arena scores (e.g., fullstack rank 21) that GPT-4o was never benchmarked on.