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Model comparison · Updated 10 Oct 2026

GPT-6 Luna vs Qwen3.8 Flash

GPT-6 Luna is about 1.5× cheaper on input ($0.10 against $0.15 per 1M tokens), though Qwen3.8 Flash is cheaper on output. GPT-6 Luna has the larger context window (1.05M against 1M tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $90.00 a month for GPT-6 Luna and $110 for Qwen3.8 Flash.

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ModelsAtlas. “GPT-6 Luna vs Qwen3.8 Flash”. Retrieved 10 Oct 2026. https://modelsatlas.com/compare/openai/gpt-6-luna/vs/qwen/3-8

Model A

GPT-6 Luna

by OpenAI · weights not marked open · GRIDC6

Input / 1M
$0.10
observed We measured
Source
Our catalogue
Retrieved
10 Oct 2026
Output / 1M$0.50
Context1.05M
vs

Model B

Qwen3.8 Flash

by Qwen (Alibaba) · weights not marked open · GRIDC5

Input / 1M
$0.15
observed We measured
Source
Our catalogue
Retrieved
1 Sep 2026
Output / 1M$0.47
Context1M

Key numbers

Standard tier · highlighted = better

GPT-6 Luna
Qwen3.8 Flash
Input / 1M tokens
$0.10
$0.15
Output / 1M tokens
$0.50
$0.47
Batch input / output
$0.05 / $0.25
Not listed
Context window
1,050,000
1,000,000
Input types
Not disclosed
Not disclosed
Weights
Not marked open
Not marked open
Tiers listed
batch, standard
standard
Prices checked
2026-10-10
2026-09-01

What it costs for real workloads

Monthly, standard tier, 30 days

Support chatbot10k chats/day · 1.5k in, 300 out
$90.00/mo
$110/mo
RAG over documents2k queries/day · 12k in, 500 out
$87.00/mo
$122/mo
Coding agent300 tasks/day · 60k in, 8k out
$90.00/mo
$115/mo

GPT-6 Luna   Qwen3.8 Flash · Derived from the standard-tier prices above, input and output tokens per request as stated, 30 days. Excludes caching discounts and batch. Try your own numbers.

On the atlas

Price band (A–H) × context band (1–6)

1 square apart. Qwen3.8 Flash (C5) sits 1 context band smaller than GPT-6 Luna (C6).

Same square as GPT-6 Luna: Llama 4 Scout ($0.10), GPT-5.6 Luna ($0.20). Same square as Qwen3.8 Flash: Claude Haiku 5.5 ($0.10), Muse Spark 1.2 Contributor ($0.10), Muse Spark 1.3 Contributor ($0.10). Open C6 · Open C5

AFreeB<$0.10C$0.10–0.30D$0.30–1E$1–3F$3–10G$10–30H$30+1<32K232–128K3128–256K4256K–1M51M6>1MINPUT PRICE PER 1M TOKENS →CONTEXT WINDOW ↑ · position within a square follows the real valueLlama 4 Scout · C6GPT-5.6 Luna · C6Claude Haiku 5.5 · C5Muse Spark 1.2 Contributor · C5Muse Spark 1.3 Contributor · C5Qwen3.8 Omni Flash · C5Llama 4 Maverick · C5Qwen3.6 Flash · C5MiniMax-01 · C5DeepSeek V4 Flash Vision Exp · C5GPT-6 LunaGPT-6 LunaQwen3.8 FlashQwen3.8 Flash
GPT-6 LunaQwen3.8 FlashNearest neighboursOpen weights
View the map as a table (2 squares)
SquarePrice bandContext bandModels
GRIDC5$0.10–0.301MQwen3.8 Flash, Claude Haiku 5.5, Muse Spark 1.2 Contributor, Muse Spark 1.3 Contributor, Qwen3.8 Omni Flash, Llama 4 Maverick, Qwen3.6 Flash, MiniMax-01, DeepSeek V4 Flash Vision Exp
GRIDC6$0.10–0.30>1MGPT-6 Luna, Llama 4 Scout, GPT-5.6 Luna

Capabilities side by side

Only what our records list

GPT-6 Luna
Qwen3.8 Flash
Vision input
Not disclosed
Not disclosed
Audio input
Not disclosed
Not disclosed
Open weights
Not marked open
Not marked open
Batch tier
Supported
Not listed
Free tier
Not listed
Not listed
Thinking tier
Not listed
Not listed

Neither record lists input types, so we do not claim any.

Which should you choose?

Editorial

Choose GPT-6 Luna if…

  • you pay by the token: it costs $0.10 per 1M input against $0.15
  • your prompts are long: it takes 1,050,000 tokens against 1,000,000
  • work can wait: it lists a batch tier and the other does not

Choose Qwen3.8 Flash if…

  • output dominates your bill: $0.47 per 1M output against $0.50

Each reason is a fact from the tables above. Picking between them is our judgement, and we do not benchmark quality: price and context are what we can measure, so test both on your own prompts before you commit.

Questions

Is GPT-6 Luna better than Qwen3.8 Flash?
We do not benchmark quality, so we cannot say. On the recorded numbers: GPT-6 Luna is about 1.5× cheaper on input ($0.10 against $0.15 per 1M tokens), though Qwen3.8 Flash is cheaper on output. GPT-6 Luna has the larger context window (1.05M against 1M tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $90.00 a month for GPT-6 Luna and $110 for Qwen3.8 Flash. Which is better for you depends on your task; test both on your own prompts.
Which is cheaper, GPT-6 Luna or Qwen3.8 Flash?
GPT-6 Luna: $0.10 against $0.15 per 1M input tokens, and $0.50 against $0.47 per 1M output, on standard pricing.
How much does each cost per 1M tokens?
GPT-6 Luna: $0.10 input and $0.50 output. Qwen3.8 Flash: $0.15 input and $0.47 output. Standard tier, USD.
Which has the larger context window?
GPT-6 Luna, with 1,050,000 tokens. Qwen3.8 Flash has 1,000,000 tokens.
Do both offer batch pricing?
GPT-6 Luna lists a batch tier, at 50% of its standard price. Qwen3.8 Flash lists no batch tier.
Can both read images or audio?
Input types recorded for GPT-6 Luna: none recorded. For Qwen3.8 Flash: none recorded. Where a record lists none we say so rather than guess; check each vendor's documentation before relying on a capability.
Is either model open-weight?
GPT-6 Luna: not marked open-weight in our records. Qwen3.8 Flash: not marked open-weight in our records.
What would each cost for a support chatbot?
At 10,000 chats a day, 1,500 input and 300 output tokens each, 30 days, standard tier: about $90.00 a month for GPT-6 Luna and $110 for Qwen3.8 Flash. This is our calculation from the listed prices, not a quote.

About the two models

GPT-6 Luna

By OpenAI. $0.10 input and $0.50 output per 1M tokens, 1.05M context, atlas square C6. Tiers listed: batch, standard.

Full specs & pricing →

Qwen3.8 Flash

By Qwen (Alibaba). $0.15 input and $0.47 output per 1M tokens, 1M context, atlas square C5. Tiers listed: standard.

Full specs & pricing →

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