Pairwise benchmark snapshot · Aug 16, 2026

GPT-5.6 Luna vs Qwen3.8 27B benchmark

Name: GPT-5.6 Luna vs Qwen3.8 27B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-5.6 Luna (OpenAI) and Qwen3.8 27B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, GPT-5.6 Luna is ahead by 68 points (1,466 vs 1,398; seed-bootstrap (Aug 16, 2026)). On SWE-bench coding, GPT-5.6 Luna resolves 61.8% versus 58.8% (seed-bootstrap (Aug 16, 2026)). GPT-5.6 Luna streams faster (188 tok/s) while GPT-5.6 Luna is the cheaper output token ($0.6/1M). GPT-5.6 Luna has the larger context window (1.1M 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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OpenAI

GPT-5.6 Luna

OpenAI 5.6 fast/cheap tier. Official API $0.20/$1.20 per 1M after the Jul 30 80% Luna cut.

Elo 1,466$0.6/1M out

Alibaba

Qwen3.8 27B

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

Elo 1,398$3.1999999999999997/1M out

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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.

GPT-5.6 Luna (10)vsQwen3.8 27B (0)

GPT-5.6 Luna: 10W (100%)Overall: GPT-5.6 LunaQwen3.8 27B: 0W (0%)

← GPT-5.6 LunaQwen3.8 27B →

GPT-5.6 Luna (5/5)

Intelligence & Reasoning

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

Preference Elo

1,466vs1,398

Coding Elo

1,458vs1,422

SWE-bench

61.8%vs58.8%

LiveBench

64.2%vs60.6%

GPQA Diamond

75.4%vs73.4%

GPT-5.6 Luna: 5WQwen3.8 27B: 0W

GPT-5.6 Luna (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

188 tok/svs152 tok/s

Time to first token

88 msvs140 ms

GPT-5.6 Luna: 2WQwen3.8 27B: 0W

GPT-5.6 Luna (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$3.2/1M

Input price

$0.1/1Mvs$0.45/1M

Context window

1.1Mvs262k

GPT-5.6 Luna: 3WQwen3.8 27B: 0W

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 AdvantageGPT-5.6 Luna 6/6

Preference Elo

GPT-5.6 Luna

68 pts advantage

Throughput Speed

GPT-5.6 Luna

36 tok/s faster

Price Efficiency

GPT-5.6 Luna

$2.60/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+5%1,466

EloHigh is better

1,398

Code Elo

High is better

+3%1,458

Code EloHigh is better

1,422

LiveBench

High is better

+6%64.2%

LiveBenchHigh is better

60.6%

SWE-bench

High is better

+5%61.8%

SWE-benchHigh is better

58.8%

GPQA

High is better

+3%75.4%

GPQAHigh is better

73.4%

TTFT

Low is better

+59%88 ms

TTFTLow is better

140 ms

Speed

High is better

+24%188 tok/s

SpeedHigh is better

152 tok/s

In $

Low is better

+350%$0.1/1M

In $Low is better

$0.45/1M

Out $

Low is better

+433%$0.6/1M

Out $Low is better

$3.2/1M

Context

High is better

+301%1.1M

ContextHigh is better

262k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 80% with GPT-5.6 Luna

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

GPT-5.6 Luna$12.50 / mo

In: $3.50Out: $9.00

Qwen3.8 27B$63.75 / mo

In: $15.75Out: $48.00

Estimated Cost Delta

GPT-5.6 Luna is estimated to save $51.25/month ($615/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GPT-5.6 Luna:Pick GPT-5.6 Luna when repo-level coding accuracy is the constraint.
2
GPT-5.6 Luna:Pick GPT-5.6 Luna when time-to-first-token matters more than peak Elo.
3
GPT-5.6 Luna:Pick GPT-5.6 Luna for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsGPT-5.6 Luna

Higher SWE-bench (61.8%).

High-volume chatGPT-5.6 Luna

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-5.6 Luna

Lower TTFT (88 ms).

Long-document RAGGPT-5.6 Luna

Larger window (1.1M).

Screenshots / visionGPT-5.6 Luna

GPT-5.6 Luna is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5.6 Luna	Higher SWE-bench (61.8%).
High-volume chat	GPT-5.6 Luna	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-5.6 Luna	Lower TTFT (88 ms).
Long-document RAG	GPT-5.6 Luna	Larger window (1.1M).
Screenshots / vision	GPT-5.6 Luna	GPT-5.6 Luna 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.

priceJul 30, 2026

GPT-5.6 Luna’s 80% cut: $0.20/$1.20 for volume chat

Luna is the OpenAI fast/cheap 5.6 SKU after Jul 30. It is not Sol. Sort by price and TTFT, not Elo.

launchAug 8, 2025

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

High-volume agents that cannot pay Sol. Compare to Luna before you assume the new cheap SKU wins.

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LIVE

OpenAI

GPT-5.6 Luna

Elo 1,466

LiveBench64.2%

SWE-bench61.8%

Speed188 tok/s

Output cost$0.6/1M

Alibaba

Qwen3.8 27B

Elo 1,398

LiveBench60.6%

SWE-bench58.8%

Speed152 tok/s

Output cost$3.2/1M

Frequently Asked Questions

Which is better overall, GPT-5.6 Luna or Qwen3.8 27B?: GPT-5.6 Luna has the higher preference Elo in our latest snapshot (1,466). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, GPT-5.6 Luna or Qwen3.8 27B?: GPT-5.6 Luna leads SWE-bench at 61.8% vs 58.8%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: GPT-5.6 Luna output tokens are $0.6/1M versus $3.2/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-5.6 Luna or Qwen3.8 27B?: GPT-5.6 Luna has the lower time-to-first-token (88 ms vs 140 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: GPT-5.6 Luna accepts 1.1M tokens versus 262k.
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. GPT-5.6 Luna and Qwen3.8 27B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-5.6 Luna matchups →|All Qwen3.8 27B matchups →

GPT-5.6 Luna vs GPT-5 mini (previous gpt-mini)Qwen3.8 27B vs Qwen 3 Max (previous qwen)Qwen QwQ 32B vs GPT-5.6 Luna Qwen 3 Max vs GPT-5.6 Luna GPT-4.5 Orion vs GPT-5.6 Luna GPT-5.6 Terra vs GPT-5.6 Luna

GPT-5.6 Luna vs Qwen3.8 27B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-5.6 Luna (10)vsQwen3.8 27B (0)

GPT-5.6 Luna: 10W (100%)Overall: GPT-5.6 LunaQwen3.8 27B: 0W (0%)

← GPT-5.6 LunaQwen3.8 27B →

GPT-5.6 Luna (5/5)

Intelligence & Reasoning

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

Preference Elo

1,466vs1,398

Coding Elo

1,458vs1,422

SWE-bench

61.8%vs58.8%

LiveBench

64.2%vs60.6%

GPQA Diamond

75.4%vs73.4%

GPT-5.6 Luna: 5WQwen3.8 27B: 0W

GPT-5.6 Luna (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

188 tok/svs152 tok/s

Time to first token

88 msvs140 ms

GPT-5.6 Luna: 2WQwen3.8 27B: 0W

GPT-5.6 Luna (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$3.2/1M

Input price

$0.1/1Mvs$0.45/1M

Context window

1.1Mvs262k

GPT-5.6 Luna: 3WQwen3.8 27B: 0W

Recommended Workload Routing

Repo / coding agentsGPT-5.6 Luna

Higher SWE-bench (61.8%).

High-volume chatGPT-5.6 Luna

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-5.6 Luna

Lower TTFT (88 ms).

Long-document RAGGPT-5.6 Luna

Larger window (1.1M).

Screenshots / visionGPT-5.6 Luna

GPT-5.6 Luna is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5.6 Luna	Higher SWE-bench (61.8%).
High-volume chat	GPT-5.6 Luna	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-5.6 Luna	Lower TTFT (88 ms).
Long-document RAG	GPT-5.6 Luna	Larger window (1.1M).
Screenshots / vision	GPT-5.6 Luna	GPT-5.6 Luna is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-5.6 Luna or Qwen3.8 27B?

GPT-5.6 Luna has the higher preference Elo in our latest snapshot (1,466). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, GPT-5.6 Luna or Qwen3.8 27B?

GPT-5.6 Luna leads SWE-bench at 61.8% vs 58.8%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

GPT-5.6 Luna output tokens are $0.6/1M versus $3.2/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-5.6 Luna or Qwen3.8 27B?

GPT-5.6 Luna has the lower time-to-first-token (88 ms vs 140 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

GPT-5.6 Luna accepts 1.1M tokens versus 262k.

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. GPT-5.6 Luna and Qwen3.8 27B 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

GPT-5.6 Luna

GPT-5.6 Luna

GPT-5.6 Luna

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

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

GPT-5.6 Luna’s 80% cut: $0.20/$1.20 for volume chat

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

Cast Your Matchup Vote

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CompareLLM Matrix

GPT-5.6 Luna

Qwen3.8 27B

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

GPT-5.6 Luna

GPT-5.6 Luna

GPT-5.6 Luna

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

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

GPT-5.6 Luna’s 80% cut: $0.20/$1.20 for volume chat

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

GPT-5.6 Luna

Qwen3.8 27B

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons