Pairwise benchmark snapshot · Aug 16, 2026

DeepSeek R1 vs Kimi K3 benchmark

Name: DeepSeek R1 vs Kimi K3 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek R1 (DeepSeek) and Kimi K3 (Moonshot) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, Kimi K3 is ahead by 170 points (1,528 vs 1,358; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Kimi K3 resolves 73.8% versus 65.2% (seed-bootstrap (Aug 1, 2026)). Kimi K3 streams faster (68 tok/s) while DeepSeek R1 is the cheaper output token ($2.5/1M). Kimi K3 has the larger context window (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 R1

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

Elo 1,358$2.5/1M out

Moonshot

Kimi K3

Moonshot AI frontier flagship reasoning and agent swarm model with 256k context and top-tier SWE-bench coding capability.

Elo 1,528$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 R1 (2)vsKimi K3 (8)

DeepSeek R1: 2W (20%)Overall: Kimi K3Kimi K3: 8W (80%)

← DeepSeek R1Kimi K3 →

Kimi K3 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,528

Coding Elo

—vs1,535

SWE-bench

65.2%vs73.8%

LiveBench

59%vs69.5%

GPQA Diamond

79.8%vs88.4%

DeepSeek R1: 0WKimi K3: 5W

Kimi K3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs68 tok/s

Time to first token

420 msvs290 ms

DeepSeek R1: 0WKimi K3: 2W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$15/1M

Input price

$0.7/1Mvs$3/1M

Context window

64kvs1M

DeepSeek R1: 2WKimi K3: 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 AdvantageKimi K3 5/6

Preference Elo

Kimi K3

170 pts advantage

Throughput Speed

Kimi K3

6 tok/s faster

Price Efficiency

DeepSeek R1

$12.50/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,358

EloHigh is better

1,528+13%

Code Elo

High is better

—

Code EloHigh is better

1,535

LiveBench

High is better

59%

LiveBenchHigh is better

69.5%+18%

SWE-bench

High is better

65.2%

SWE-benchHigh is better

73.8%+13%

GPQA

High is better

79.8%

GPQAHigh is better

88.4%+11%

TTFT

Low is better

420 ms

TTFTLow is better

290 ms+45%

Speed

High is better

62 tok/s

SpeedHigh is better

68 tok/s+10%

In $

Low is better

+329%$0.7/1M

In $Low is better

$3/1M

Out $

Low is better

+500%$2.5/1M

Out $Low is better

$15/1M

Context

High is better

64k

ContextHigh is better

1M+1538%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 81% with DeepSeek R1

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

Kimi K3$330.00 / mo

In: $105.00Out: $225.00

Estimated Cost Delta

DeepSeek R1 is estimated to save $268.00/month ($3,216/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Kimi K3:Pick Kimi K3 when repo-level coding accuracy is the constraint.
2
DeepSeek R1:Pick DeepSeek R1 when you are optimizing output cost.
3
Kimi K3:Pick Kimi K3 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsKimi K3

Higher SWE-bench (73.8%).

High-volume chatDeepSeek R1

Lower output list price ($2.5/1M).

Voice / low-latency UIKimi K3

Lower TTFT (290 ms).

Long-document RAGKimi K3

Larger window (1M).

Screenshots / visionKimi K3

Kimi K3 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Kimi K3	Higher SWE-bench (73.8%).
High-volume chat	DeepSeek R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Kimi K3	Lower TTFT (290 ms).
Long-document RAG	Kimi K3	Larger window (1M).
Screenshots / vision	Kimi K3	Kimi K3 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJun 8, 2026

Kimi K3: Moonshot’s long-context open-weight competitive row

Jun 2026. The Kimi vs GPT hub remaps to the top Moonshot Elo vs top OpenAI Elo.

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.

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LIVE

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

Moonshot

Kimi K3

Elo 1,528

LiveBench69.5%

SWE-bench73.8%

Speed68 tok/s

Output cost$15/1M

Frequently Asked Questions

Which is better overall, DeepSeek R1 or Kimi K3?: Kimi K3 has the higher preference Elo in our latest snapshot (1,528). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek R1 or Kimi K3?: Kimi K3 leads SWE-bench at 73.8% vs 65.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek R1 output tokens are $2.5/1M versus $15/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek R1 or Kimi K3?: Kimi K3 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?: Kimi K3 accepts 1M 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 Kimi K3 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 Kimi K3 matchups →

DeepSeek R1 vs DeepSeek V3 (previous deepseek)DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)Kimi K3 vs MoonshotAI: Kimi K2.5 (previous kimi)DeepSeek V4 Flash vs Kimi K3 DeepSeek V4 Pro vs Kimi K3 DeepSeek Coder V2 vs DeepSeek R1

DeepSeek R1 vs Kimi K3 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (2)vsKimi K3 (8)

DeepSeek R1: 2W (20%)Overall: Kimi K3Kimi K3: 8W (80%)

← DeepSeek R1Kimi K3 →

Kimi K3 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,528

Coding Elo

—vs1,535

SWE-bench

65.2%vs73.8%

LiveBench

59%vs69.5%

GPQA Diamond

79.8%vs88.4%

DeepSeek R1: 0WKimi K3: 5W

Kimi K3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs68 tok/s

Time to first token

420 msvs290 ms

DeepSeek R1: 0WKimi K3: 2W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$15/1M

Input price

$0.7/1Mvs$3/1M

Context window

64kvs1M

DeepSeek R1: 2WKimi K3: 1W

Recommended Workload Routing

Repo / coding agentsKimi K3

Higher SWE-bench (73.8%).

High-volume chatDeepSeek R1

Lower output list price ($2.5/1M).

Voice / low-latency UIKimi K3

Lower TTFT (290 ms).

Long-document RAGKimi K3

Larger window (1M).

Screenshots / visionKimi K3

Kimi K3 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Kimi K3	Higher SWE-bench (73.8%).
High-volume chat	DeepSeek R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Kimi K3	Lower TTFT (290 ms).
Long-document RAG	Kimi K3	Larger window (1M).
Screenshots / vision	Kimi K3	Kimi K3 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek R1 or Kimi K3?

Kimi K3 has the higher preference Elo in our latest snapshot (1,528). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek R1 or Kimi K3?

Kimi K3 leads SWE-bench at 73.8% vs 65.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek R1 output tokens are $2.5/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek R1 or Kimi K3?

Kimi K3 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?

Kimi K3 accepts 1M 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 Kimi K3 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

Kimi K3

Kimi K3

DeepSeek R1

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Kimi K3: Moonshot’s long-context open-weight competitive row

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

DeepSeek R1

Kimi K3

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

Kimi K3

Kimi K3

DeepSeek R1

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Kimi K3: Moonshot’s long-context open-weight competitive row

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

Kimi K3

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons