Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

DeepSeek: DeepSeek V3.2 Exp vs GPT-4o mini benchmark

Name: DeepSeek: DeepSeek V3.2 Exp vs GPT-4o mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek: DeepSeek V3.2 Exp (DeepSeek) and GPT-4o mini (OpenAI) using the latest snapshots we have as of Aug 17, 2026. DeepSeek: DeepSeek V3.2 Exp wins on output price at $0.41/1M. DeepSeek: DeepSeek V3.2 Exp has the larger context window (164k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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DeepSeek

DeepSeek: DeepSeek V3.2 Exp

Auto-discovered from OpenRouter (deepseek/deepseek-v3.2-exp). Preview until a second source matches.

$0.41/1M out

OpenAI

GPT-4o mini

Legacy small OpenAI model. Useful as a cheap baseline.

4o MiniElo 1,272$0.6/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek: DeepSeek V3.2 Exp (2)vsGPT-4o mini (7)

DeepSeek: DeepSeek V3.2 Exp: 2W (22%)Overall: GPT-4o miniGPT-4o mini: 7W (78%)

← DeepSeek: DeepSeek V3.2 ExpGPT-4o mini →

GPT-4o mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,272

Coding Elo

—vs—

SWE-bench

—vs41.2%

LiveBench

—vs48.1%

GPQA Diamond

—vs60.1%

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-4o mini: 4W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs160 tok/s

Time to first token

—vs130 ms

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-4o mini: 2W

DeepSeek: DeepSeek V3.2 Exp (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.41/1Mvs$0.6/1M

Input price

$0.27/1Mvs$0.15/1M

Context window

164kvs128k

DeepSeek: DeepSeek V3.2 Exp: 2WGPT-4o mini: 1W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGPT-4o mini 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

DeepSeek: DeepSeek V3.2 Exp

$0.19/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,272

LiveBench

High is better

—

LiveBenchHigh is better

48.1%

SWE-bench

High is better

—

SWE-benchHigh is better

41.2%

GPQA

High is better

—

GPQAHigh is better

60.1%

TTFT

Low is better

—

TTFTLow is better

130 ms

Speed

High is better

—

SpeedHigh is better

160 tok/s

In $

Low is better

$0.27 / 1M

In $Low is better

$0.15 / 1M+80%

Out $

Low is better

+46%$0.41 / 1M

Out $Low is better

$0.60 / 1M

Context

High is better

+28%164k

ContextHigh is better

128k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 9% with GPT-4o mini

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

DeepSeek: DeepSeek V3.2 Exp$15.60 / mo

In: $9.45Out: $6.15

GPT-4o mini$14.25 / mo

In: $5.25Out: $9

Estimated Cost Delta

GPT-4o mini is estimated to save $1.35/month ($16/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek: DeepSeek V3.2 Exp:Pick DeepSeek: DeepSeek V3.2 Exp when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.2 Exp

Lower output list price ($0.41/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek: DeepSeek V3.2 Exp

Larger window (164k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	DeepSeek: DeepSeek V3.2 Exp	Lower output list price ($0.41/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek: DeepSeek V3.2 Exp	Larger window (164k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

DeepSeek

DeepSeek: DeepSeek V3.2 Exp

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.41/1M

OpenAI

GPT-4o mini

Elo 1,272

LiveBench48.1%

SWE-bench41.2%

Speed160 tok/s

Output cost$0.6/1M

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: DeepSeek: DeepSeek V3.2 Exp output tokens are $0.41/1M versus $0.6/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?: We do not have TTFT for both models.
Which has the larger context window?: DeepSeek: DeepSeek V3.2 Exp accepts 164k tokens versus 128k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. DeepSeek: DeepSeek V3.2 Exp and GPT-4o mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek: DeepSeek V3.2 Exp matchups →|All GPT-4o mini matchups →

GPT-4o mini vs OpenAI o1-mini (next gpt-mini)GPT-5 vs GPT-4o mini GPT-4.5 Orion vs GPT-4o mini GPT-5.6 Sol vs GPT-4o mini GPT-5.6 Terra vs GPT-4o mini DeepSeek V4 Pro vs GPT-4o mini

DeepSeek: DeepSeek V3.2 Exp vs GPT-4o mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek: DeepSeek V3.2 Exp (2)vsGPT-4o mini (7)

DeepSeek: DeepSeek V3.2 Exp: 2W (22%)Overall: GPT-4o miniGPT-4o mini: 7W (78%)

← DeepSeek: DeepSeek V3.2 ExpGPT-4o mini →

GPT-4o mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,272

Coding Elo

—vs—

SWE-bench

—vs41.2%

LiveBench

—vs48.1%

GPQA Diamond

—vs60.1%

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-4o mini: 4W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs160 tok/s

Time to first token

—vs130 ms

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-4o mini: 2W

DeepSeek: DeepSeek V3.2 Exp (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.41/1Mvs$0.6/1M

Input price

$0.27/1Mvs$0.15/1M

Context window

164kvs128k

DeepSeek: DeepSeek V3.2 Exp: 2WGPT-4o mini: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.2 Exp

Lower output list price ($0.41/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek: DeepSeek V3.2 Exp

Larger window (164k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	DeepSeek: DeepSeek V3.2 Exp	Lower output list price ($0.41/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek: DeepSeek V3.2 Exp	Larger window (164k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

DeepSeek: DeepSeek V3.2 Exp output tokens are $0.41/1M versus $0.6/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek: DeepSeek V3.2 Exp or GPT-4o mini?

We do not have TTFT for both models.

Which has the larger context window?

DeepSeek: DeepSeek V3.2 Exp accepts 164k tokens versus 128k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. DeepSeek: DeepSeek V3.2 Exp and GPT-4o mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.