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

DeepSeek Coder V2 vs OpenAI: GPT-5.5 (batch) benchmark

Name: DeepSeek Coder V2 vs OpenAI: GPT-5.5 (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek Coder V2 (DeepSeek) and OpenAI: GPT-5.5 (batch) (OpenAI) using the latest snapshots we have as of Aug 17, 2026. DeepSeek Coder V2 wins on output price at $0.28/1M. OpenAI: GPT-5.5 (batch) has the larger context window (1.1M 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: GPT-5.5 (batch)

Auto-discovered from OpenRouter (openai/gpt-5.5:batch). Preview until a second source matches.

$15/1M 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 Coder V2 (9)vsOpenAI: GPT-5.5 (batch) (1)

DeepSeek Coder V2: 9W (90%)Overall: DeepSeek Coder V2OpenAI: GPT-5.5 (batch): 1W (10%)

← DeepSeek Coder V2OpenAI: GPT-5.5 (batch) →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs—

Coding Elo

1,442vs—

SWE-bench

60.5%vs—

LiveBench

58.6%vs—

GPQA Diamond

70.2%vs—

DeepSeek Coder V2: 5WOpenAI: GPT-5.5 (batch): 0W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs—

Time to first token

290 msvs—

DeepSeek Coder V2: 2WOpenAI: GPT-5.5 (batch): 0W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$15/1M

Input price

$0.14/1Mvs$2.5/1M

Context window

128kvs1.1M

DeepSeek Coder V2: 2WOpenAI: GPT-5.5 (batch): 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 Coder V2 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

DeepSeek Coder V2

$14.72/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,365

EloHigh is better

—

Code Elo

High is better

1,442

Code EloHigh is better

—

LiveBench

High is better

58.6%

LiveBenchHigh is better

—

SWE-bench

High is better

60.5%

SWE-benchHigh is better

—

GPQA

High is better

70.2%

GPQAHigh is better

—

TTFT

Low is better

290 ms

TTFTLow is better

—

Speed

High is better

75 tok/s

SpeedHigh is better

—

In $

Low is better

+1686%$0.14/1M

In $Low is better

$2.5/1M

Out $

Low is better

+5257%$0.28/1M

Out $Low is better

$15/1M

Context

High is better

128k

ContextHigh is better

1.1M+720%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 97% 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: GPT-5.5 (batch)$312.50 / mo

In: $87.50Out: $225.00

Estimated Cost Delta

DeepSeek Coder V2 is estimated to save $303.40/month ($3,641/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek Coder V2:Pick DeepSeek Coder V2 when you are optimizing output cost.
2
OpenAI: GPT-5.5 (batch):Pick OpenAI: GPT-5.5 (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek Coder V2

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.5 (batch)

Larger window (1.1M).

Screenshots / visionOpenAI: GPT-5.5 (batch)

OpenAI: GPT-5.5 (batch) 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 Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.5 (batch)	Larger window (1.1M).
Screenshots / vision	OpenAI: GPT-5.5 (batch)	OpenAI: GPT-5.5 (batch) is the side marked multimodal in the catalog.

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CompareLLM Matrix

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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: GPT-5.5 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$15/1M

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or OpenAI: GPT-5.5 (batch)?: 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 Coder V2 or OpenAI: GPT-5.5 (batch)?: 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 Coder V2 output tokens are $0.28/1M versus $15/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek Coder V2 or OpenAI: GPT-5.5 (batch)?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.5 (batch) accepts 1.1M 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: GPT-5.5 (batch) 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: GPT-5.5 (batch) matchups →

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

DeepSeek Coder V2 vs OpenAI: GPT-5.5 (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (9)vsOpenAI: GPT-5.5 (batch) (1)

DeepSeek Coder V2: 9W (90%)Overall: DeepSeek Coder V2OpenAI: GPT-5.5 (batch): 1W (10%)

← DeepSeek Coder V2OpenAI: GPT-5.5 (batch) →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs—

Coding Elo

1,442vs—

SWE-bench

60.5%vs—

LiveBench

58.6%vs—

GPQA Diamond

70.2%vs—

DeepSeek Coder V2: 5WOpenAI: GPT-5.5 (batch): 0W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs—

Time to first token

290 msvs—

DeepSeek Coder V2: 2WOpenAI: GPT-5.5 (batch): 0W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$15/1M

Input price

$0.14/1Mvs$2.5/1M

Context window

128kvs1.1M

DeepSeek Coder V2: 2WOpenAI: GPT-5.5 (batch): 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek Coder V2

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.5 (batch)

Larger window (1.1M).

Screenshots / visionOpenAI: GPT-5.5 (batch)

OpenAI: GPT-5.5 (batch) 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 Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.5 (batch)	Larger window (1.1M).
Screenshots / vision	OpenAI: GPT-5.5 (batch)	OpenAI: GPT-5.5 (batch) is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or OpenAI: GPT-5.5 (batch)?

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 Coder V2 or OpenAI: GPT-5.5 (batch)?

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 Coder V2 output tokens are $0.28/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek Coder V2 or OpenAI: GPT-5.5 (batch)?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.5 (batch) accepts 1.1M 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: GPT-5.5 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.