Pairwise benchmark snapshot · Aug 16, 2026

DeepSeek Coder V2 vs OpenAI: o1 benchmark

Name: DeepSeek Coder V2 vs OpenAI: o1 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek Coder V2 (DeepSeek) and OpenAI: o1 (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o1 is ahead by 147 points (1,512 vs 1,365; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, DeepSeek Coder V2 resolves 60.5% versus 48.9% (seed-bootstrap (Aug 1, 2026)). DeepSeek Coder V2 streams faster (75 tok/s) while DeepSeek Coder V2 is the cheaper output token ($0.28/1M). OpenAI: o1 has the larger context window (200k 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 Coder V2

DeepSeek open-weight Mixture-of-Experts coding model supporting 338 programming languages and 128k context.

Elo 1,365$0.28/1M out

OpenAI

OpenAI: o1

Auto-discovered from OpenRouter (openai/o1). Preview until a second source matches.

Elo 1,512$60/1M out

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Model A

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (5)vsOpenAI: o1 (5)

DeepSeek Coder V2: 5W (50%)Overall: Even matchupOpenAI: o1: 5W (50%)

← DeepSeek Coder V2OpenAI: o1 →

OpenAI: o1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,512

Coding Elo

1,442vs1,485

SWE-bench

60.5%vs48.9%

LiveBench

58.6%vs65.4%

GPQA Diamond

70.2%vs78%

DeepSeek Coder V2: 1WOpenAI: o1: 4W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs45 tok/s

Time to first token

290 msvs420 ms

DeepSeek Coder V2: 2WOpenAI: o1: 0W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$60/1M

Input price

$0.14/1Mvs$15/1M

Context window

128kvs200k

DeepSeek Coder V2: 2WOpenAI: o1: 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 AdvantageEven 3–3

Preference Elo

OpenAI: o1

147 pts advantage

Throughput Speed

DeepSeek Coder V2

30 tok/s faster

Price Efficiency

DeepSeek Coder V2

$59.72/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,365

EloHigh is better

1,512+11%

Code Elo

High is better

1,442

Code EloHigh is better

1,485+3%

LiveBench

High is better

58.6%

LiveBenchHigh is better

65.4%+12%

SWE-bench

High is better

+24%60.5%

SWE-benchHigh is better

48.9%

GPQA

High is better

70.2%

GPQAHigh is better

78%+11%

TTFT

Low is better

+45%290 ms

TTFTLow is better

420 ms

Speed

High is better

+67%75 tok/s

SpeedHigh is better

45 tok/s

In $

Low is better

+10614%$0.14/1M

In $Low is better

$15/1M

Out $

Low is better

+21329%$0.28/1M

Out $Low is better

$60/1M

Context

High is better

128k

ContextHigh is better

200k+56%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 99% with DeepSeek Coder V2

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek Coder V2$9.10 / mo

In: $4.90Out: $4.20

OpenAI: o1$1,425.00 / mo

In: $525.00Out: $900.00

Estimated Cost Delta

DeepSeek Coder V2 is estimated to save $1,415.90/month ($16,991/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek Coder V2:Pick DeepSeek Coder V2 when repo-level coding accuracy is the constraint.
2
DeepSeek Coder V2:Pick DeepSeek Coder V2 when time-to-first-token matters more than peak Elo.
3
OpenAI: o1:Pick OpenAI: o1 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsDeepSeek Coder V2

Higher SWE-bench (60.5%).

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UIDeepSeek Coder V2

Lower TTFT (290 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

OpenAI: o1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek Coder V2	Higher SWE-bench (60.5%).
High-volume chat	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	DeepSeek Coder V2	Lower TTFT (290 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 is the side marked multimodal in the catalog.

Community Sentiment

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LIVE

DeepSeek

DeepSeek Coder V2

Elo 1,365

LiveBench58.6%

SWE-bench60.5%

Speed75 tok/s

Output cost$0.28/1M

OpenAI

OpenAI: o1

Elo 1,512

LiveBench65.4%

SWE-bench48.9%

Speed45 tok/s

Output cost$60/1M

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or OpenAI: o1?: OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek Coder V2 or OpenAI: o1?: DeepSeek Coder V2 leads SWE-bench at 60.5% vs 48.9%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek Coder V2 output tokens are $0.28/1M versus $60/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek Coder V2 or OpenAI: o1?: DeepSeek Coder V2 has the lower time-to-first-token (290 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: OpenAI: o1 accepts 200k tokens versus 128k.
Can I self-host either model?: DeepSeek Coder V2 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 Coder V2 and OpenAI: o1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek Coder V2 matchups →|All OpenAI: o1 matchups →

DeepSeek Coder V2 vs DeepSeek V3 (next deepseek)OpenAI: o1 vs GPT-4o (previous gpt-flagship)OpenAI: o1 vs GPT-4.5 Orion (next gpt-flagship)DeepSeek V4 Flash vs OpenAI: o1 GPT-5 vs OpenAI: o1 DeepSeek V4 Pro vs OpenAI: o1

DeepSeek Coder V2 vs OpenAI: o1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (5)vsOpenAI: o1 (5)

DeepSeek Coder V2: 5W (50%)Overall: Even matchupOpenAI: o1: 5W (50%)

← DeepSeek Coder V2OpenAI: o1 →

OpenAI: o1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,512

Coding Elo

1,442vs1,485

SWE-bench

60.5%vs48.9%

LiveBench

58.6%vs65.4%

GPQA Diamond

70.2%vs78%

DeepSeek Coder V2: 1WOpenAI: o1: 4W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs45 tok/s

Time to first token

290 msvs420 ms

DeepSeek Coder V2: 2WOpenAI: o1: 0W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$60/1M

Input price

$0.14/1Mvs$15/1M

Context window

128kvs200k

DeepSeek Coder V2: 2WOpenAI: o1: 1W

Recommended Workload Routing

Repo / coding agentsDeepSeek Coder V2

Higher SWE-bench (60.5%).

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UIDeepSeek Coder V2

Lower TTFT (290 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

OpenAI: o1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek Coder V2	Higher SWE-bench (60.5%).
High-volume chat	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	DeepSeek Coder V2	Lower TTFT (290 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or OpenAI: o1?

OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek Coder V2 or OpenAI: o1?

DeepSeek Coder V2 leads SWE-bench at 60.5% vs 48.9%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek Coder V2 output tokens are $0.28/1M versus $60/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek Coder V2 or OpenAI: o1?

DeepSeek Coder V2 has the lower time-to-first-token (290 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

OpenAI: o1 accepts 200k tokens versus 128k.

Can I self-host either model?

DeepSeek Coder V2 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 Coder V2 and OpenAI: o1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.