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

DeepSeek R1 vs OpenAI: o4 Mini (batch) benchmark

Name: DeepSeek R1 vs OpenAI: o4 Mini (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek R1 (DeepSeek) and OpenAI: o4 Mini (batch) (OpenAI) using the latest snapshots we have as of Aug 16, 2026. OpenAI: o4 Mini (batch) wins on output price at $2.2/1M. OpenAI: o4 Mini (batch) 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 R1

Open-weights reasoning model trained with large-scale RL.

Elo 1,358$2.5/1M out

OpenAI

OpenAI: o4 Mini (batch)

Auto-discovered from OpenRouter (openai/o4-mini:batch). Preview until a second source matches.

$2.2/1M 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 R1 (6)vsOpenAI: o4 Mini (batch) (3)

DeepSeek R1: 6W (67%)Overall: DeepSeek R1OpenAI: o4 Mini (batch): 3W (33%)

← DeepSeek R1OpenAI: o4 Mini (batch) →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs—

Coding Elo

—vs—

SWE-bench

65.2%vs—

LiveBench

59%vs—

GPQA Diamond

79.8%vs—

DeepSeek R1: 4WOpenAI: o4 Mini (batch): 0W

DeepSeek R1 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs—

Time to first token

420 msvs—

DeepSeek R1: 2WOpenAI: o4 Mini (batch): 0W

OpenAI: o4 Mini (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$2.2/1M

Input price

$0.7/1Mvs$0.55/1M

Context window

64kvs200k

DeepSeek R1: 0WOpenAI: o4 Mini (batch): 3W

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 R1 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

OpenAI: o4 Mini (batch)

$0.30/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,358

EloHigh is better

—

LiveBench

High is better

59%

LiveBenchHigh is better

—

SWE-bench

High is better

65.2%

SWE-benchHigh is better

—

GPQA

High is better

79.8%

GPQAHigh is better

—

TTFT

Low is better

420 ms

TTFTLow is better

—

Speed

High is better

62 tok/s

SpeedHigh is better

—

In $

Low is better

$0.7/1M

In $Low is better

$0.55/1M+27%

Out $

Low is better

$2.5/1M

Out $Low is better

$2.2/1M+14%

Context

High is better

64k

ContextHigh is better

200k+213%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 16% with OpenAI: o4 Mini (batch)

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek R1$62.00 / mo

In: $24.50Out: $37.50

OpenAI: o4 Mini (batch)$52.25 / mo

In: $19.25Out: $33.00

Estimated Cost Delta

OpenAI: o4 Mini (batch) is estimated to save $9.75/month ($117/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: o4 Mini (batch):Pick OpenAI: o4 Mini (batch) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: o4 Mini (batch)

Lower output list price ($2.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o4 Mini (batch)

Larger window (200k).

Screenshots / visionOpenAI: o4 Mini (batch)

OpenAI: o4 Mini (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	OpenAI: o4 Mini (batch)	Lower output list price ($2.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o4 Mini (batch)	Larger window (200k).
Screenshots / vision	OpenAI: o4 Mini (batch)	OpenAI: o4 Mini (batch) is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJan 20, 2025

DeepSeek R1 stays as the open-weights RL baseline

Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.

Community Sentiment

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LIVE

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

OpenAI

OpenAI: o4 Mini (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$2.2/1M

Frequently Asked Questions

Which is better overall, DeepSeek R1 or OpenAI: o4 Mini (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 R1 or OpenAI: o4 Mini (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?: OpenAI: o4 Mini (batch) output tokens are $2.2/1M versus $2.5/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek R1 or OpenAI: o4 Mini (batch)?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: o4 Mini (batch) accepts 200k tokens versus 64k.
Can I self-host either model?: DeepSeek R1 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 R1 and OpenAI: o4 Mini (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek R1 matchups →|All OpenAI: o4 Mini (batch) matchups →

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

DeepSeek R1 vs OpenAI: o4 Mini (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (6)vsOpenAI: o4 Mini (batch) (3)

DeepSeek R1: 6W (67%)Overall: DeepSeek R1OpenAI: o4 Mini (batch): 3W (33%)

← DeepSeek R1OpenAI: o4 Mini (batch) →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs—

Coding Elo

—vs—

SWE-bench

65.2%vs—

LiveBench

59%vs—

GPQA Diamond

79.8%vs—

DeepSeek R1: 4WOpenAI: o4 Mini (batch): 0W

DeepSeek R1 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs—

Time to first token

420 msvs—

DeepSeek R1: 2WOpenAI: o4 Mini (batch): 0W

OpenAI: o4 Mini (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$2.2/1M

Input price

$0.7/1Mvs$0.55/1M

Context window

64kvs200k

DeepSeek R1: 0WOpenAI: o4 Mini (batch): 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: o4 Mini (batch)

Lower output list price ($2.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: o4 Mini (batch)

Larger window (200k).

Screenshots / visionOpenAI: o4 Mini (batch)

OpenAI: o4 Mini (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	OpenAI: o4 Mini (batch)	Lower output list price ($2.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: o4 Mini (batch)	Larger window (200k).
Screenshots / vision	OpenAI: o4 Mini (batch)	OpenAI: o4 Mini (batch) is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek R1 or OpenAI: o4 Mini (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 R1 or OpenAI: o4 Mini (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?

OpenAI: o4 Mini (batch) output tokens are $2.2/1M versus $2.5/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek R1 or OpenAI: o4 Mini (batch)?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: o4 Mini (batch) accepts 200k tokens versus 64k.

Can I self-host either model?

DeepSeek R1 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 R1 and OpenAI: o4 Mini (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

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

OpenAI: o4 Mini (batch)

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

OpenAI: o4 Mini (batch)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

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

OpenAI: o4 Mini (batch)

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

OpenAI: o4 Mini (batch)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons