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

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  3. Qwen3.8 27B (Aug 14): dense enough to self-host, not a frontier MoE
Qwen3.8 27B (Aug 14): dense enough to self-host, not a frontier MoE
launchVerified Dispatch
CompareLLM Intelligence Desk·Aug 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.

Search intent: qwen3.8 27b

Evaluated Models:Qwen3.8 27B(Alibaba)
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Verified Benchmark Scorecard

Qwen3.8 27B vs Grok 3 Benchmark Breakdown

Full Head-to-Head
Elo Quality1,398Qwen3.8 27B
SWE-bench58.8%Coding ability
Speed152 tok/sInference rate
Token Cost$3.20per 1M reply

79% Lower Token Cost Advantage

Qwen3.8 27B costs $3.20/1M compared to Grok 3 at $15.00/1M.

Preference EloGeneral quality
+7.0 Grok 3
Qwen3.8 27B1,398
Grok 31,405
SWE-bench VerifiedSoftware engineering %
+7.4 Qwen3.8 27B
Qwen3.8 27B58.8%
Grok 351.4%
GPQA DiamondPhD-level science %
+0.8 Grok 3
Qwen3.8 27B73.4%
Grok 374.2%
ThroughputTokens / sec speed
+64.0 Qwen3.8 27B
Qwen3.8 27B152 tok/s
Grok 388 tok/s
Output Priceper 1M reply tokens
Qwen3.8 27B ($11.80 cheaper)
Qwen3.8 27B$3.2/1M
Grok 3$15/1M
Benchmark MetricQwen3.8 27BGrok 3Advantage
Preference EloGeneral quality1,3981,405+7.0 Grok 3
SWE-bench VerifiedSoftware engineering %58.8%51.4%+7.4 Qwen3.8 27B
GPQA DiamondPhD-level science %73.4%74.2%+0.8 Grok 3
ThroughputTokens / sec speed152 tok/s88 tok/s+64.0 Qwen3.8 27B
Output Priceper 1M reply tokens$3.2/1M$15/1MQwen3.8 27B ($11.80 cheaper)
Executive Key Takeaway
Alibaba open-weight 27B drop. Local/open-weight lists should see it. It will not win frontier-agents.

Alibaba published Qwen3.8 27B open weights on Aug 14 2026. It is dense enough to self-host and is not a frontier MoE. On CompareLLM it belongs on best-local-llm and open-weights lists, not on cheapest-frontier. If you expected Qwen3 Max quality in 27B, the pair page versus Qwen 3 Max will disappoint you honestly.

27B is a hardware decision

We do not publish VRAM tables. “Best local llm” here means open-weight rows ranked on Elo and SWE-bench, not “fits in 24GB.” Read the license and your box.

Empirical Evaluation & Architectural Analysis

Empirical evaluations recorded across the CompareLLM Leaderboard highlight how parameter scaling and inference optimization impact production throughput and cost-per-token economics. Reference the interactive scorecard above for verified snapshots or inspect the dedicated qwen-3-8-27b dossier.

Don’t merge 3.8 into 3-max aliases

Different slugs. Ingest matching the wrong Qwen name is how catalogs lie. Attach leftovers in admin.

Strategic Deployment Recommendation

  • Production Workloads: For enterprise workloads requiring strict reliability, cross-reference Top Coding LLMs and Cheapest High-Quality LLMs.
  • Direct Pair Comparison: Explore the live pairwise breakdown at /best/best-local-llm.
  • Architectural Stacks: Recommended architectural configurations can be evaluated on the CompareLLM Stack Engine.

Frequently Asked Questions

Is this an CompareLLM lab test score? No. Linked model dossiers and compare showdowns reflect dated snapshots gathered from named public evaluation benchmarks. Seed catalog entries remain transparently timestamped until daily ingest updates them.

Where can I see live comparisons for this model? View the showdown at /best/best-local-llm.

What primary search query does this briefing answer? qwen3.8 27b.

Share Analysis:
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Head-to-Head Showdowns for Mentioned Models

Benchmark MatchupQwen3.8 27B vs Claude Opus 4.5
Benchmark MatchupQwen3.8 27B vs Claude Opus 4.6
Back to All DispatchesExplore Comparison Matrix