Pairwise benchmark snapshot · Aug 17, 2026

Command A vs DeepSeek R1 benchmark

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

This page compares Command A (Cohere) and DeepSeek R1 (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, DeepSeek R1 is ahead by 14 points (1,358 vs 1,344; lmarena (Aug 17, 2026)). On SWE-bench coding, DeepSeek R1 resolves 65.2% versus 42.6% (swebench (Aug 17, 2026)). Command A streams faster (118 tok/s) while DeepSeek R1 is the cheaper output token ($2.5/1M). Command A has the larger context window (256k 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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Cohere

Command A

Cohere enterprise RAG and tool-use model.

Elo 1,344$10/1M out

DeepSeek

DeepSeek R1

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

Elo 1,358$2.5/1M 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.

Command A (3)vsDeepSeek R1 (6)

Command A: 3W (33%)Overall: DeepSeek R1DeepSeek R1: 6W (67%)

← Command ADeepSeek R1 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,344vs1,358

Coding Elo

—vs—

SWE-bench

42.6%vs65.2%

LiveBench

56.2%vs59%

GPQA Diamond

66%vs79.8%

Command A: 0WDeepSeek R1: 4W

Command A (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

118 tok/svs62 tok/s

Time to first token

175 msvs420 ms

Command A: 2WDeepSeek R1: 0W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$2.5/1M

Input price

$2.5/1Mvs$0.7/1M

Context window

256kvs64k

Command A: 1WDeepSeek R1: 2W

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

DeepSeek R1

14 pts advantage

Throughput Speed

Command A

56 tok/s faster

Price Efficiency

DeepSeek R1

$7.50/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,344

EloHigh is better

1,358+1%

LiveBench

High is better

56.2%

LiveBenchHigh is better

59%+5%

SWE-bench

High is better

42.6%

SWE-benchHigh is better

65.2%+53%

GPQA

High is better

66%

GPQAHigh is better

79.8%+21%

TTFT

Low is better

+140%175 ms

TTFTLow is better

420 ms

Speed

High is better

+90%118 tok/s

SpeedHigh is better

62 tok/s

In $

Low is better

$2.5/1M

In $Low is better

$0.7/1M+257%

Out $

Low is better

$10/1M

Out $Low is better

$2.5/1M+300%

Context

High is better

+300%256k

ContextHigh is better

64k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 74% 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)

Command A$237.50 / mo

In: $87.50Out: $150.00

DeepSeek R1$62.00 / mo

In: $24.50Out: $37.50

Estimated Cost Delta

DeepSeek R1 is estimated to save $175.50/month ($2,106/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek R1:Pick DeepSeek R1 when repo-level coding accuracy is the constraint.
2
Command A:Pick Command A when time-to-first-token matters more than peak Elo.
3
DeepSeek R1:Pick DeepSeek R1 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek R1

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

Voice / low-latency UICommand A

Lower TTFT (175 ms).

Long-document RAGCommand A

Larger window (256k).

Screenshots / visionDeepSeek R1

DeepSeek R1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	DeepSeek R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Command A	Lower TTFT (175 ms).
Long-document RAG	Command A	Larger window (256k).
Screenshots / vision	DeepSeek R1	DeepSeek R1 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchMar 13, 2025

Command A: Cohere’s enterprise RAG and tool-use row

Mar 2025. RAG and tools, not a frontier Elo play. Listed so “command a benchmark” has a sourced page.

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

Cohere

Command A

Elo 1,344

LiveBench56.2%

SWE-bench42.6%

Speed118 tok/s

Output cost$10/1M

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

Frequently Asked Questions

Which is better overall, Command A or DeepSeek R1?: DeepSeek R1 has the higher preference Elo in our latest snapshot (1,358). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Command A or DeepSeek R1?: DeepSeek R1 leads SWE-bench at 65.2% vs 42.6%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek R1 output tokens are $2.5/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, Command A or DeepSeek R1?: Command A has the lower time-to-first-token (175 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Command A accepts 256k 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. Command A and DeepSeek R1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Command A matchups →|All DeepSeek R1 matchups →

DeepSeek R1 vs DeepSeek V3 (previous deepseek)DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)DeepSeek V4 Flash vs DeepSeek R1 DeepSeek Coder V2 vs DeepSeek R1 DeepSeek V3 vs Command A Mistral Large 3 vs DeepSeek R1

Command A vs DeepSeek R1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Command A (3)vsDeepSeek R1 (6)

Command A: 3W (33%)Overall: DeepSeek R1DeepSeek R1: 6W (67%)

← Command ADeepSeek R1 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,344vs1,358

Coding Elo

—vs—

SWE-bench

42.6%vs65.2%

LiveBench

56.2%vs59%

GPQA Diamond

66%vs79.8%

Command A: 0WDeepSeek R1: 4W

Command A (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

118 tok/svs62 tok/s

Time to first token

175 msvs420 ms

Command A: 2WDeepSeek R1: 0W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$2.5/1M

Input price

$2.5/1Mvs$0.7/1M

Context window

256kvs64k

Command A: 1WDeepSeek R1: 2W

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek R1

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

Voice / low-latency UICommand A

Lower TTFT (175 ms).

Long-document RAGCommand A

Larger window (256k).

Screenshots / visionDeepSeek R1

DeepSeek R1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	DeepSeek R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Command A	Lower TTFT (175 ms).
Long-document RAG	Command A	Larger window (256k).
Screenshots / vision	DeepSeek R1	DeepSeek R1 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Command A or DeepSeek R1?

DeepSeek R1 has the higher preference Elo in our latest snapshot (1,358). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Command A or DeepSeek R1?

DeepSeek R1 leads SWE-bench at 65.2% vs 42.6%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek R1 output tokens are $2.5/1M versus $10/1M. Input prices and retry rates still move the real bill.

Which is faster, Command A or DeepSeek R1?

Command A has the lower time-to-first-token (175 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Command A accepts 256k 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. Command A and DeepSeek R1 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

DeepSeek R1

Command A

DeepSeek R1

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Command A: Cohere’s enterprise RAG and tool-use row

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Command A

DeepSeek R1

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

DeepSeek R1

Command A

DeepSeek R1

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Command A: Cohere’s enterprise RAG and tool-use row

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Command A

DeepSeek R1

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons