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

DeepSeek: DeepSeek V3.2 Exp vs GPT-5 benchmark

Name: DeepSeek: DeepSeek V3.2 Exp vs GPT-5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek: DeepSeek V3.2 Exp (DeepSeek) and GPT-5 (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. GPT-5 has the larger context window (400k 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-5

OpenAI flagship reasoning model for 2025–26. Strong general preference Elo and multimodal coverage.

Elo 1,558$10/1M out

GPT-5 Inference Compute Profile

Inference-Time Compute & Reasoning EffortDynamic CoT

GPT-5 Reasoning Scaler & Token Billing Simulator

Param: reasoning_effort

Reasoning models scale test-time compute by generating hidden chain-of-thought (CoT) tokens. These tokens are billed at standard output rates and directly expand latency (TTFT) in exchange for higher GPQA Diamond and SWE-bench Verified problem resolve rates.

Estimated TTFT

290 ms

1.0x (Standard eval)

CoT Thinking Tokens

~1,500

Billed as output tokens

Est. Cost / 1k Calls

$18.63

5.1x base invoice

STEM / SWE Boost

+4.5%

GPQA & SWE-bench scaling

Medium (Standard) Operational Profile

Default evaluation baseline balancing reasoning depth with stream rate.

Direct Provider APIOpenAI

"reasoning_effort": "medium"

OpenRouter Unified APIUnified Gateway

"reasoning": {
  "effort": "medium",
  "max_tokens": 1500
}

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

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-5 (8)

DeepSeek: DeepSeek V3.2 Exp: 2W (20%)Overall: GPT-5GPT-5: 8W (80%)

← DeepSeek: DeepSeek V3.2 ExpGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,558

Coding Elo

—vs1,540

SWE-bench

—vs68.4%

LiveBench

—vs69.8%

GPQA Diamond

—vs85.2%

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-5: 5W

GPT-5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs78 tok/s

Time to first token

—vs290 ms

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-5: 2W

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

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.41/1Mvs$10/1M

Input price

$0.27/1Mvs$1.25/1M

Context window

164kvs400k

DeepSeek: DeepSeek V3.2 Exp: 2WGPT-5: 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-5 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

DeepSeek: DeepSeek V3.2 Exp

$9.59/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,558

Code Elo

High is better

—

Code EloHigh is better

1,540

LiveBench

High is better

—

LiveBenchHigh is better

69.8%

SWE-bench

High is better

—

SWE-benchHigh is better

68.4%

GPQA

High is better

—

GPQAHigh is better

85.2%

TTFT

Low is better

—

TTFTLow is better

290 ms

Speed

High is better

—

SpeedHigh is better

78 tok/s

In $

Low is better

+363%$0.27 / 1M

In $Low is better

$1.25 / 1M

Out $

Low is better

+2339%$0.41 / 1M

Out $Low is better

$10.00 / 1M

Context

High is better

164k

ContextHigh is better

400k+144%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 92% with DeepSeek: DeepSeek V3.2 Exp

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-5$193.75 / mo

In: $43.75Out: $150

Estimated Cost Delta

DeepSeek: DeepSeek V3.2 Exp is estimated to save $178.15/month ($2,138/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 RAGGPT-5

Larger window (400k).

Screenshots / visionGPT-5

GPT-5 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	GPT-5	Larger window (400k).
Screenshots / vision	GPT-5	GPT-5 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchAug 8, 2025

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Still a common compare target. 5.6 Sol replaced it as the buy; GPT-5 stays for old URLs.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

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CompareLLM Matrix

Verified head-to-head card

LIVE

DeepSeek

DeepSeek: DeepSeek V3.2 Exp

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.41/1M

OpenAI

GPT-5

Elo 1,558

LiveBench69.8%

SWE-bench68.4%

Speed78 tok/s

Output cost$10/1M

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.2 Exp or GPT-5?: 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-5?: 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 $10/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek: DeepSeek V3.2 Exp or GPT-5?: We do not have TTFT for both models.
Which has the larger context window?: GPT-5 accepts 400k tokens versus 164k.
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-5 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-5 matchups →

GPT-5 vs GPT-4.5 Orion (previous gpt-flagship)GPT-5 vs GPT-5.6 Sol (next gpt-flagship)GPT-5.6 Terra vs GPT-5 DeepSeek V4 Pro vs GPT-5 DeepSeek V4 Flash vs GPT-5 GPT-5 mini vs GPT-5

DeepSeek: DeepSeek V3.2 Exp vs GPT-5 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-5 (8)

DeepSeek: DeepSeek V3.2 Exp: 2W (20%)Overall: GPT-5GPT-5: 8W (80%)

← DeepSeek: DeepSeek V3.2 ExpGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,558

Coding Elo

—vs1,540

SWE-bench

—vs68.4%

LiveBench

—vs69.8%

GPQA Diamond

—vs85.2%

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-5: 5W

GPT-5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs78 tok/s

Time to first token

—vs290 ms

DeepSeek: DeepSeek V3.2 Exp: 0WGPT-5: 2W

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

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.41/1Mvs$10/1M

Input price

$0.27/1Mvs$1.25/1M

Context window

164kvs400k

DeepSeek: DeepSeek V3.2 Exp: 2WGPT-5: 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 RAGGPT-5

Larger window (400k).

Screenshots / visionGPT-5

GPT-5 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	GPT-5	Larger window (400k).
Screenshots / vision	GPT-5	GPT-5 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.2 Exp or GPT-5?

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-5?

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 $10/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek: DeepSeek V3.2 Exp or GPT-5?

We do not have TTFT for both models.

Which has the larger context window?

GPT-5 accepts 400k tokens versus 164k.

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-5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

GPT-5 Reasoning Scaler & Token Billing Simulator

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

DeepSeek: DeepSeek V3.2 Exp

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek: DeepSeek V3.2 Exp

GPT-5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

GPT-5 Reasoning Scaler & Token Billing Simulator

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

DeepSeek: DeepSeek V3.2 Exp

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek: DeepSeek V3.2 Exp

GPT-5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons