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  3. Cohere: Command R7B (12-2024) vs DeepSeek V4 Pro

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

Cohere: Command R7B (12-2024) vs DeepSeek V4 Pro benchmark

In this head-to-head showdown, Cohere: Command R7B (12-2024) is more budget-friendly at $0.15/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Both Cohere: Command R7B (12-2024) and DeepSeek V4 Pro present distinct architectural strengths. Compare the verified benchmark matrix below to choose the model tailored to your specific application requirements.
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Cohere
Cohere: Command R7B (12-2024)

Auto-discovered from OpenRouter (cohere/command-r7b-12-2024). Preview until a second source matches.

$0.15/1M out
DeepSeek
DeepSeek V4 Pro

Open-weight-adjacent DeepSeek flagship. High reasoning density per dollar.

Elo 1,536$3.9600000000000004/1M out

DeepSeek V4 Pro Thinking Depth & Cost Scaler

Simulate accuracy gains vs added response time & token cost

Mode: Medium (Full RL CoT)

Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.

Thinking Delay
410 ms
Standard speed
Reasoning Depth
~2,800
Internal tokens
Cost / 1k Calls
$12.94
7.0× standard bill
Accuracy Boost
+6.5% accuracy
STEM & SWE-bench
Top Rival Showdowns for Cohere: Command R7B (12-2024)
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek R1
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar Leader

Cohere: Command R7B (12-2024)

$0.15 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

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 V4 Pro 5/6
Head-to-Head Comparison

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Cohere: Command R7B (12-2024) (2)vsDeepSeek V4 Pro (8)
Cohere: Command R7B (12-2024): 2W (20%)Overall: DeepSeek V4 ProDeepSeek V4 Pro: 8W (80%)
← Cohere: Command R7B (12-2024)DeepSeek V4 Pro →
DeepSeek V4 Pro (5/5)

Intelligence & Reasoning

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

Preference Elo
—vs1,536
Coding Elo
—vs1,544
SWE-bench
—vs71.6%
LiveBench
—vs70.1%
GPQA Diamond
—vs84%
Cohere: Command R7B (12-2024): 0WDeepSeek V4 Pro: 5W
DeepSeek V4 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
—vs70 tok/s
Time to first token
—vs410 ms
Cohere: Command R7B (12-2024): 0WDeepSeek V4 Pro: 2W
Cohere: Command R7B (12-2024) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$0.15/1Mvs$3.96/1M
Input price
$0.0375/1Mvs$1.32/1M
Context window
128kvs1M
Cohere: Command R7B (12-2024): 2WDeepSeek V4 Pro: 1W

Side-by-Side Benchmark Matrix

Preference Elo
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro1,536
lmarena · Aug 17, 2026
Coding Elo
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro1,544
lmarena · Aug 17, 2026
LiveBench
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro70.1%
livebench · Aug 17, 2026
SWE-bench
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro71.6%
swebench · Aug 17, 2026
GPQA Diamond
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro84%
seed-bootstrap · Aug 1, 2026
Time to first token
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro410 ms
seed-bootstrap · Aug 1, 2026
Output speed
Cohere: Command R7B (12-2024)—
DeepSeek V4 Pro70 tok/s
seed-bootstrap · Aug 1, 2026
Input priceCohere: Command R7B (12-2024) (+$1.28/1M)
Cohere: Command R7B (12-2024)$0.0375/1M
openrouter · Aug 17, 2026
DeepSeek V4 Pro$1.32/1M
openrouter · Aug 17, 2026
Output priceCohere: Command R7B (12-2024) (+$3.81/1M)
Cohere: Command R7B (12-2024)$0.15/1M
openrouter · Aug 17, 2026
DeepSeek V4 Pro$3.96/1M
openrouter · Aug 17, 2026
Context windowDeepSeek V4 Pro (+921k)
Cohere: Command R7B (12-2024)128k
openrouter · Aug 17, 2026
DeepSeek V4 Pro1M
openrouter · Aug 17, 2026
BenchmarkCohere: Command R7B (12-2024)DeepSeek V4 ProAdvantage Delta
Preference Elo—
1,536
lmarena · Aug 17, 2026
—
Coding Elo—
1,544
lmarena · Aug 17, 2026
—
LiveBench—
70.1%
livebench · Aug 17, 2026
—
SWE-bench—
71.6%
swebench · Aug 17, 2026
—
GPQA Diamond—
84%
seed-bootstrap · Aug 1, 2026
—
Time to first token—
410 ms
seed-bootstrap · Aug 1, 2026
—
Output speed—
70 tok/s
seed-bootstrap · Aug 1, 2026
—
Input price
$0.0375/1M
openrouter · Aug 17, 2026
$1.32/1M
openrouter · Aug 17, 2026
Cohere: Command R7B (12-2024) (+$1.28/1M)
Output price
$0.15/1M
openrouter · Aug 17, 2026
$3.96/1M
openrouter · Aug 17, 2026
Cohere: Command R7B (12-2024) (+$3.81/1M)
Context window
128k
openrouter · Aug 17, 2026
1M
openrouter · Aug 17, 2026
DeepSeek V4 Pro (+921k)
Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 97% with Cohere: Command R7B (12-2024)
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Cohere: Command R7B (12-2024)$3.56 / mo
In: $1.31Out: $2.25
DeepSeek V4 Pro$105.60 / mo
In: $46.2Out: $59.4
Estimated Cost Delta

Cohere: Command R7B (12-2024) is estimated to save $102.04/month ($1,224/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Cohere: Command R7B (12-2024):Pick Cohere: Command R7B (12-2024) when you are optimizing output cost.
  • 2
    DeepSeek V4 Pro:Pick DeepSeek V4 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatCohere: Command R7B (12-2024)

Lower output list price ($0.15/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek V4 Pro

Larger window (1M).

Screenshots / visionDeepSeek V4 Pro

DeepSeek V4 Pro is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatCohere: Command R7B (12-2024)Lower output list price ($0.15/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGDeepSeek V4 ProLarger window (1M).
Screenshots / visionDeepSeek V4 ProDeepSeek V4 Pro is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news
compareJun 13, 2026

DeepSeek vs Claude: the cheap-versus-frontier question, remapped

Top DeepSeek vs top Anthropic Elo. Usually V4 Pro vs Opus 5. License and invoice decide as much as Elo.

launchJun 12, 2026

DeepSeek V4 Pro: high reasoning density per dollar

2026-06 open-weight-adjacent flagship. The usual cheap-vs-Claude question starts here.

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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CompareLLM Matrix

Verified head-to-head card

LIVE
VS
Cohere

Cohere: Command R7B (12-2024)

Elo n/a
LiveBench—
SWE-bench—
Speed—
Output cost$0.15/1M
DeepSeek

DeepSeek V4 Pro

Elo 1,536
LiveBench70.1%
SWE-bench71.6%
Speed70 tok/s
Output cost$3.96/1M

Frequently Asked Questions

Which is better overall, Cohere: Command R7B (12-2024) or DeepSeek V4 Pro?
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, Cohere: Command R7B (12-2024) or DeepSeek V4 Pro?
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?
Cohere: Command R7B (12-2024) output tokens are $0.15/1M versus $3.96/1M. Input prices and retry rates still move the real bill.
Which is faster, Cohere: Command R7B (12-2024) or DeepSeek V4 Pro?
We do not have TTFT for both models.
Which has the larger context window?
DeepSeek V4 Pro accepts 1M tokens versus 128k.
Can I self-host either model?
DeepSeek V4 Pro 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. Cohere: Command R7B (12-2024) and DeepSeek V4 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • compare · Jun 13, 2026

    DeepSeek vs Claude: the cheap-versus-frontier question, remapped

  • launch · Jun 12, 2026

    DeepSeek V4 Pro: high reasoning density per dollar

  • launch · Jan 20, 2025

    DeepSeek R1 stays as the open-weights RL baseline

Similar Head-to-Head Comparisons

All Cohere: Command R7B (12-2024) matchups →|All DeepSeek V4 Pro matchups →
DeepSeek V4 Pro vs DeepSeek R1 (previous deepseek)DeepSeek V4 Pro vs DeepSeek V4 Flash (next deepseek)Command A vs DeepSeek V4 ProDeepSeek V3 vs DeepSeek V4 ProDeepSeek Coder V2 vs DeepSeek V4 ProClaude Opus 4.5 vs DeepSeek V4 Pro