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Every score has a dated snapshot.

  1. Home
  2. Comparisons
  3. DeepSeek V3 vs GPT-5

Pairwise benchmark snapshot · Aug 16, 2026

DeepSeek V3 vs GPT-5 benchmark

This page compares DeepSeek V3 (DeepSeek) and GPT-5 (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, GPT-5 is ahead by 248 points (1,558 vs 1,310; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, GPT-5 resolves 68.4% versus 48.6% (seed-bootstrap (Aug 1, 2026)). GPT-5 streams faster (78 tok/s) while DeepSeek V3 is the cheaper output token ($1.03/1M). 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.

Quick answer

DeepSeek V3 vs GPT-5 is a dated snapshot, not a lab score. GPT-5 leads preference Elo (1,558 vs 1,310). GPT-5 leads SWE-bench coding. DeepSeek V3 is the cheaper output token. Elo is crowd preference, not an exam. Pick the column that matches the job.
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DeepSeek

DeepSeek V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310$1.0287/1M out

OpenAI

GPT-5

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

Elo 1,558$10/1M out

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A
Model B
Quick vs:vs Claude Opus 4.5vs Claude Opus 4.6vs Claude Sonnet 4.5vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek V3 (2)vsGPT-5 (8)
DeepSeek V3: 2W (20%)Overall: GPT-5GPT-5: 8W (80%)
← DeepSeek V3GPT-5 →
GPT-5 (5/5)

Intelligence & Reasoning

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

Preference Elo
1,310vs1,558
Coding Elo
—vs1,540
SWE-bench
48.6%vs68.4%
LiveBench
55.4%vs69.8%
GPQA Diamond
59.1%vs85.2%
DeepSeek V3: 0WGPT-5: 5W
GPT-5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
66 tok/svs78 tok/s
Time to first token
380 msvs290 ms
DeepSeek V3: 0WGPT-5: 2W
DeepSeek V3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$1.03/1Mvs$10/1M
Input price
$0.26/1Mvs$1.25/1M
Context window
164kvs400k
DeepSeek V3: 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

GPT-5

248 pts advantage

Throughput Speed

GPT-5

12 tok/s faster

Price Efficiency

DeepSeek V3

$8.97/1M cheaper

Full Benchmark Score Matrix

—
Elo
High is better
1,310
EloHigh is better
1,558+19%
Code Elo
High is better
—
Code EloHigh is better
1,540
LiveBench
High is better
55.4%
LiveBenchHigh is better
69.8%+26%
SWE-bench
High is better
48.6%
SWE-benchHigh is better
68.4%+41%
GPQA
High is better
59.1%
GPQAHigh is better
85.2%+44%
TTFT
Low is better
380 ms
TTFTLow is better
290 ms+31%
Speed
High is better
66 tok/s
SpeedHigh is better
78 tok/s+18%
In $
Low is better
+386%$0.26/1M
In $Low is better
$1.25/1M
Out $
Low is better
+872%$1.03/1M
Out $Low is better
$10/1M
Context
High is better
164k
ContextHigh is better
400k+144%
Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 87% with DeepSeek V3
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
DeepSeek V3$24.44 / mo
In: $9.01Out: $15.43
GPT-5$193.75 / mo
In: $43.75Out: $150.00
Estimated Cost Delta

DeepSeek V3 is estimated to save $169.31/month ($2,032/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    GPT-5:Pick GPT-5 when repo-level coding accuracy is the constraint.
  • 2
    DeepSeek V3:Pick DeepSeek V3 when you are optimizing output cost.
  • 3
    GPT-5:Pick GPT-5 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsGPT-5

Higher SWE-bench (68.4%).

High-volume chatDeepSeek V3

Lower output list price ($1.03/1M).

Voice / low-latency UIGPT-5

Lower TTFT (290 ms).

Long-document RAGGPT-5

Larger window (400k).

Screenshots / visionGPT-5

GPT-5 is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsGPT-5Higher SWE-bench (68.4%).
High-volume chatDeepSeek V3Lower output list price ($1.03/1M).
Voice / low-latency UIGPT-5Lower TTFT (290 ms).
Long-document RAGGPT-5Larger window (400k).
Screenshots / visionGPT-5GPT-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.

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CompareLLM Matrix

Verified head-to-head card

LIVE
VS
DeepSeek

DeepSeek V3

Elo 1,310
LiveBench55.4%
SWE-bench48.6%
Speed66 tok/s
Output cost$1.03/1M
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 V3 or GPT-5?
GPT-5 has the higher preference Elo in our latest snapshot (1,558). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek V3 or GPT-5?
GPT-5 leads SWE-bench at 68.4% vs 48.6%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?
DeepSeek V3 output tokens are $1.03/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek V3 or GPT-5?
GPT-5 has the lower time-to-first-token (290 ms vs 380 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?
GPT-5 accepts 400k tokens versus 164k.
Can I self-host either model?
DeepSeek V3 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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 V3 and GPT-5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · Aug 8, 2025

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

Similar Head-to-Head Comparisons

All DeepSeek V3 matchups →|All GPT-5 matchups →
DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)GPT-5 vs GPT-4.5 Orion (previous gpt-flagship)GPT-5 vs GPT-5.6 Sol (next gpt-flagship)DeepSeek V4 Pro vs GPT-5GPT-5.6 Terra vs GPT-5