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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  3. Cohere: Command R7B (12-2024) vs Qwen3.8 27B

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

Cohere: Command R7B (12-2024) vs Qwen3.8 27B 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 Qwen3.8 27B present distinct architectural strengths. Compare the verified benchmark matrix below to choose the model tailored to your specific application requirements.
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Verified Head-to-Head Advantage Breakdown

3 direct benchmark disciplines evaluated across capability, speed, and cost

Cohere: Command R7B (12-2024) (2)Qwen3.8 27B (1)
Cohere: Command R7B (12-2024)
2 of 3 Wins
✓Input price✓Output price
Qwen3.8 27B
1 of 3 Wins
✓Context window
Cohere
Leads 2 of 3 metrics
Cohere: Command R7B (12-2024)

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

$0.15/1M out
Alibaba
Leads 1 of 3 metrics
Qwen3.8 27B

Alibaba open-weight 27B drop dated Aug 14 2026. Dense enough to self-host; not a frontier MoE.

27B DenseElo 1,398$3.1999999999999997/1M out
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 V4 Pro
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderCohere: Command R7B (12-2024) Wins

Cohere: Command R7B (12-2024)

$0.15 / 1M output

Capability Percentiles

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

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect
0–100 %ile
Head-to-Head Comparison

Overall Matchup Breakdown

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

Cohere: Command R7B (12-2024) (2)vsQwen3.8 27B (8)
Cohere: Command R7B (12-2024): 2W (20%)Overall: Qwen3.8 27BQwen3.8 27B: 8W (80%)
← Cohere: Command R7B (12-2024)Qwen3.8 27B →
🏆Qwen3.8 27B(5/5)

Intelligence & Reasoning

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

Benchmark
Cohere: Command R7B (12-2024)vsQwen3.8 27B
Preference Elo
—vs1,398
Coding Elo
—vs1,422
SWE-bench
—vs58.8%
LiveBench
—vs60.6%
GPQA Diamond
—vs73.4%
Cohere: Command R7B (12-2024): 0WQwen3.8 27B: 5W
🏆Qwen3.8 27B(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Cohere: Command R7B (12-2024)vsQwen3.8 27B
Output speed
—vs152 tok/s
Time to first token
—vs140 ms
Cohere: Command R7B (12-2024): 0WQwen3.8 27B: 2W
🏆Cohere: Command R7B (12-2024)(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Cohere: Command R7B (12-2024)vsQwen3.8 27B
Output price
$0.15/1Mvs$3.2/1M+$3.05/1M
Input price
$0.038/1Mvs$0.45/1M+$0.413/1M
Context window
128kvs262k+134k
Cohere: Command R7B (12-2024): 2WQwen3.8 27B: 1W

Side-by-Side Benchmark Matrix

Preference Elo
Cohere: Command R7B (12-2024)—
Qwen3.8 27B1,398
lmarena · Aug 16, 2026
Coding Elo
Cohere: Command R7B (12-2024)—
Qwen3.8 27B1,422
lmarena · Aug 16, 2026
LiveBench
Cohere: Command R7B (12-2024)—
Qwen3.8 27B60.6%
livebench · Aug 16, 2026
SWE-bench
Cohere: Command R7B (12-2024)—
Qwen3.8 27B58.8%
swebench · Aug 16, 2026
GPQA Diamond
Cohere: Command R7B (12-2024)—
Qwen3.8 27B73.4%
seed-bootstrap · Aug 16, 2026
Time to first token
Cohere: Command R7B (12-2024)—
Qwen3.8 27B140 ms
seed-bootstrap · Aug 16, 2026
Output speed
Cohere: Command R7B (12-2024)—
Qwen3.8 27B152 tok/s
seed-bootstrap · Aug 16, 2026
Input price+$0.413/1M
Cohere: Command R7B (12-2024)$0.038/1M
openrouter · Aug 17, 2026
Qwen3.8 27B$0.45/1M
openrouter · Aug 17, 2026
Output price+$3.05/1M
Cohere: Command R7B (12-2024)$0.15/1M
openrouter · Aug 17, 2026
Qwen3.8 27B$3.2/1M
openrouter · Aug 17, 2026
Context window+134k
Cohere: Command R7B (12-2024)128k
openrouter · Aug 17, 2026
Qwen3.8 27B262k
openrouter · Aug 17, 2026
BenchmarkCohere: Command R7B (12-2024)Qwen3.8 27BAdvantage Delta
Preference Elo—
1,398
lmarena · Aug 16, 2026
—
Coding Elo—
1,422
lmarena · Aug 16, 2026
—
LiveBench—
60.6%
livebench · Aug 16, 2026
—
SWE-bench—
58.8%
swebench · Aug 16, 2026
—
GPQA Diamond—
73.4%
seed-bootstrap · Aug 16, 2026
—
Time to first token—
140 ms
seed-bootstrap · Aug 16, 2026
—
Output speed—
152 tok/s
seed-bootstrap · Aug 16, 2026
—
Input price
$0.038/1M
openrouter · Aug 17, 2026
$0.45/1M
openrouter · Aug 17, 2026
+$0.413/1M
Output price
$0.15/1M
openrouter · Aug 17, 2026
$3.2/1M
openrouter · Aug 17, 2026
+$3.05/1M
Context window
128k
openrouter · Aug 17, 2026
262k
openrouter · Aug 17, 2026
+134k
Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 94% 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
Qwen3.8 27B$63.75 / mo
In: $15.75Out: $48
Estimated Cost Delta

Cohere: Command R7B (12-2024) is estimated to save $60.19/month ($722/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.

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 RAGQwen3.8 27B

Larger window (262k).

Screenshots / visionQwen3.8 27B

Qwen3.8 27B 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 RAGQwen3.8 27BLarger window (262k).
Screenshots / visionQwen3.8 27BQwen3.8 27B is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news
launchAug 14, 2026

Qwen3.8 27B (Aug 14): dense enough to self-host, not a frontier MoE

Alibaba open-weight 27B drop. Local/open-weight lists should see it. It will not win frontier-agents.

Community Sentiment

Cast Your Matchup Vote

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Cohere

Cohere: Command R7B (12-2024)

Elo n/a
SWE-bench—
Speed (tok/s)128k
Input / 1M Tokens$0.038/1M
Output / 1M Tokens$0.15/1M
Alibaba

Qwen3.8 27B

Elo 1,398
SWE-bench58.8%
Speed (tok/s)152 tok/s
Input / 1M Tokens$0.45/1M
Output / 1M Tokens$3.2/1M

Frequently Asked Questions

Which is better overall, Cohere: Command R7B (12-2024) or Qwen3.8 27B?
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 Qwen3.8 27B?
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 $3.2/1M. Input prices and retry rates still move the real bill.
Which is faster, Cohere: Command R7B (12-2024) or Qwen3.8 27B?
We do not have TTFT for both models.
Which has the larger context window?
Qwen3.8 27B accepts 262k tokens versus 128k.
Can I self-host either model?
Qwen3.8 27B 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 Qwen3.8 27B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · Aug 14, 2026

    Qwen3.8 27B (Aug 14): dense enough to self-host, not a frontier MoE

Similar Head-to-Head Comparisons

All Cohere: Command R7B (12-2024) matchups →|All Qwen3.8 27B matchups →
Qwen 3 Max vs Qwen3.8 27BQwen QwQ 32B vs Qwen3.8 27BQwen3 235B vs Qwen3.8 27BQwen 2.5 Plus vs Qwen3.8 27BCommand A vs Qwen3.8 27BQwen 2.5 Coder 32B vs Qwen3.8 27B