DeepSeek V3.2 vs GPT-5 Mini
DeepSeek V3.2 and GPT-5 Mini both target cost-efficient, high-throughput use cases, but they solve different problems. DeepSeek V3.2 is text-only with a 131K context window and DeepSeek Sparse Attention for efficient reasoning; GPT-5 Mini adds image and file input with a 400K context window and mandatory reasoning effort levels. The price gap and the modality gap are the two things that should actually decide this for you.
Spec vs spec
| Spec | DeepSeek V3.2 | GPT-5 Mini |
|---|---|---|
| Context window | 131K | 400K |
| Max output | 64K | 128K |
| Input modalities | text | text, image, file |
| Output modalities | text | text |
| Knowledge cutoff | — | May 31, 2024 |
| Released | Dec 1, 2025 | Aug 7, 2025 |
| Reasoning | optional | always on |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
deepseek/deepseek-v3.2
Input · 1M tokens
$0.229 + 3%$0.236
Output · 1M tokens
$0.343 + 3%$0.353
Cache read · 1M tokens
$0.023 + 3%$0.024
FEE — FLAT, EVERY MODEL3%
openai/gpt-5-mini
Input · 1M tokens
$0.250 + 3%$0.258
Output · 1M tokens
$2.00 + 3%$2.06
Cache read · 1M tokens
$0.025 + 3%$0.026
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
deepseek/deepseek-v3.2Cheaper
$3.06
$2.97 provider + 3%
openai/gpt-5-mini
$6.70
$6.50 provider + 3%
Benchmarks
Design Arena categories where both models have results. Higher Elo and lower rank win.
| DeepSeek V3.2 | GPT-5 Mini | |||
|---|---|---|---|---|
| Category | Elo | Rank | Elo | Rank |
| 3D | 1210 | #41 | 1114 | #73 |
| ASCII art | 1129 | #42 | 1173 | #33 |
| Code | 1213 | #48 | 1164 | #64 |
| Data viz | 1203 | #48 | 1167 | #62 |
| Game dev | 1197 | #50 | 1194 | #54 |
| SVG | 1089 | #54 | 1149 | #42 |
| UI components | 1203 | #47 | 1161 | #57 |
| Websites | 1217 | #46 | 1167 | #62 |
Head-to-head preference voting. How we filter and rank
Pricing math on a real workload
Run 10M input tokens and 2M output tokens through each model. DeepSeek V3.2 costs $2.97 total on OpenKey; GPT-5 Mini costs $6.50. That's a 2.2x gap driven almost entirely by output pricing: DeepSeek's completion rate is $0.3432/M from the provider ($0.353496/M on OpenKey after the 3% fee), while GPT-5 Mini's completion rate is $2.00/M ($2.06/M on OpenKey). Input pricing is nearly a wash — DeepSeek at $0.2288/M vs GPT-5 Mini at $0.25/M, a ratio of 0.92. If your workload is output-heavy (long completions, code generation, verbose reasoning traces), DeepSeek's price advantage compounds fast. Both models run through OpenKey with the same key and the same flat 3% fee on top of provider list price, so the comparison above is the real cost difference, not a platform markup difference.
Coding and design benchmarks
Across Design Arena's eight tracked categories, DeepSeek V3.2 ranks better (lower rank number = better) in six: 3d (rank 41 vs 73), codecategories (48 vs 64), dataviz (48 vs 62), gamedev (50 vs 54), uicomponent (47 vs 57), and website (46 vs 62). GPT-5 Mini ranks better in two: asciiart (rank 33 vs 42) and svg (rank 42 vs 54). For general UI, web, and data-viz code generation, DeepSeek V3.2 has the edge. If your work leans toward SVG generation or ASCII-art style output, GPT-5 Mini tests better.
Context and modality
GPT-5 Mini's context window is 400,000 tokens against DeepSeek V3.2's 131,072 — a context ratio of 0.33, meaning DeepSeek holds about a third of GPT-5 Mini's window. GPT-5 Mini also accepts image and file input alongside text, while DeepSeek V3.2 is text-in, text-out only. Max completion length favors GPT-5 Mini too, at 128,000 tokens versus DeepSeek's 64,000. If your task involves ingesting large documents, screenshots, or PDFs, or you need very long single-turn context, GPT-5 Mini is the only one of the two that can do it.
Reasoning and tool use
GPT-5 Mini has mandatory reasoning with four effort levels (high, medium, low, minimal), defaulting to medium — you can't turn reasoning off. DeepSeek V3.2 supports reasoning but doesn't require it (default disabled), so you can run it in a plain fast-completion mode when you don't need chain-of-thought. DeepSeek also exposes a wider parameter set for fine control — top_k, min_p, repetition_penalty, logit_bias, logprobs — where GPT-5 Mini's supported parameter list is narrower and more reasoning-centric. If you want a switch between cheap-and-fast and deliberate reasoning on the same model, DeepSeek gives you that control; GPT-5 Mini's effort levels give you a similar knob but reasoning stays on.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume code generation (web/UI/dataviz) | DeepSeek V3.2 | Better rank in codecategories (48 vs 64), dataviz (48 vs 62), and uicomponent (47 vs 57) |
| Document analysis with images or PDFs | GPT-5 Mini | Only model here with image and file input modalities |
| Long-context single-turn tasks | GPT-5 Mini | 400K context window vs DeepSeek's 131,072 |
| Cost-sensitive output-heavy workloads | DeepSeek V3.2 | $2.97 vs $6.50 on a 10M-in/2M-out workload |
| SVG or ASCII-art generation | GPT-5 Mini | Better rank in svg (42 vs 54) and asciiart (33 vs 42) |
| Toggling reasoning on/off per request | DeepSeek V3.2 | Reasoning is optional (default disabled); GPT-5 Mini's reasoning is mandatory |
Questions
- Which model is cheaper for a typical workload?
- DeepSeek V3.2 costs $2.97 for 10M input tokens plus 2M output tokens on OpenKey, versus $6.50 for GPT-5 Mini on the same workload — DeepSeek is roughly 2.2x cheaper, mostly because its output rate is $0.3432/M provider price versus $2.00/M for GPT-5 Mini.
- Does DeepSeek V3.2 beat GPT-5 Mini on every benchmark?
- No. DeepSeek V3.2 ranks better in 6 of the 8 Design Arena categories (3d, codecategories, dataviz, gamedev, uicomponent, website). GPT-5 Mini ranks better in asciiart (rank 33 vs 42) and svg (rank 42 vs 54).
- Which model supports image input?
- GPT-5 Mini does — its input modalities include text, image, and file. DeepSeek V3.2 is text-to-text only, so if your pipeline needs to send screenshots or PDFs, GPT-5 Mini is the only option of the two.
- How much bigger is GPT-5 Mini's context window?
- GPT-5 Mini supports 400,000 tokens of context versus DeepSeek V3.2's 131,072 — a context ratio of 0.33, meaning DeepSeek's window is about a third the size. GPT-5 Mini's max output is also larger at 128,000 tokens versus DeepSeek's 64,000.