Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

DeepSeek V3 vs OpenAI: GPT-5.1-Codex benchmark

Name: DeepSeek V3 vs OpenAI: GPT-5.1-Codex AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek V3 (DeepSeek) and OpenAI: GPT-5.1-Codex (OpenAI) using the latest snapshots we have as of Aug 16, 2026. DeepSeek V3 wins on output price at $1.03/1M. OpenAI: GPT-5.1-Codex 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 V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310$1.0287/1M out

OpenAI

OpenAI: GPT-5.1-Codex

Auto-discovered from OpenRouter (openai/gpt-5.1-codex). Preview until a second source matches.

$10/1M 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 V3 (8)vsOpenAI: GPT-5.1-Codex (1)

DeepSeek V3: 8W (89%)Overall: DeepSeek V3OpenAI: GPT-5.1-Codex: 1W (11%)

← DeepSeek V3OpenAI: GPT-5.1-Codex →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WOpenAI: GPT-5.1-Codex: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WOpenAI: GPT-5.1-Codex: 0W

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: 2WOpenAI: GPT-5.1-Codex: 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 AdvantageDeepSeek V3 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

DeepSeek V3

$8.97/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,310

EloHigh is better

—

LiveBench

High is better

55.4%

LiveBenchHigh is better

—

SWE-bench

High is better

48.6%

SWE-benchHigh is better

—

GPQA

High is better

59.1%

GPQAHigh is better

—

TTFT

Low is better

380 ms

TTFTLow is better

—

Speed

High is better

66 tok/s

SpeedHigh is better

—

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

OpenAI: GPT-5.1-Codex$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
DeepSeek V3:Pick DeepSeek V3 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek V3

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.1-Codex

Larger window (400k).

Screenshots / visionOpenAI: GPT-5.1-Codex

OpenAI: GPT-5.1-Codex 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 V3	Lower output list price ($1.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.1-Codex	Larger window (400k).
Screenshots / vision	OpenAI: GPT-5.1-Codex	OpenAI: GPT-5.1-Codex is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

DeepSeek

DeepSeek V3

Elo 1,310

LiveBench55.4%

SWE-bench48.6%

Speed66 tok/s

Output cost$1.03/1M

OpenAI

OpenAI: GPT-5.1-Codex

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$10/1M

Frequently Asked Questions

Which is better overall, DeepSeek V3 or OpenAI: GPT-5.1-Codex?: 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 V3 or OpenAI: GPT-5.1-Codex?: 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 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 OpenAI: GPT-5.1-Codex?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.1-Codex 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 OpenAI: GPT-5.1-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek V3 matchups →|All OpenAI: GPT-5.1-Codex matchups →

DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)GPT-5 vs DeepSeek V3 DeepSeek V4 Pro vs DeepSeek V3 GPT-4.5 Orion vs DeepSeek V3 GPT-5.6 Sol vs DeepSeek V3

DeepSeek V3 vs OpenAI: GPT-5.1-Codex benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek V3 (8)vsOpenAI: GPT-5.1-Codex (1)

DeepSeek V3: 8W (89%)Overall: DeepSeek V3OpenAI: GPT-5.1-Codex: 1W (11%)

← DeepSeek V3OpenAI: GPT-5.1-Codex →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WOpenAI: GPT-5.1-Codex: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WOpenAI: GPT-5.1-Codex: 0W

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: 2WOpenAI: GPT-5.1-Codex: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek V3

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.1-Codex

Larger window (400k).

Screenshots / visionOpenAI: GPT-5.1-Codex

OpenAI: GPT-5.1-Codex 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 V3	Lower output list price ($1.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.1-Codex	Larger window (400k).
Screenshots / vision	OpenAI: GPT-5.1-Codex	OpenAI: GPT-5.1-Codex is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek V3 or OpenAI: GPT-5.1-Codex?

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 V3 or OpenAI: GPT-5.1-Codex?

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 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 OpenAI: GPT-5.1-Codex?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.1-Codex 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 OpenAI: GPT-5.1-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.