Gemini 3.8 Flash vs GPT-5.6 Luna

As of October 21, 2026, Gemini 3.8 Flash costs 275% more per input token than GPT-5.6 Luna ($0.75 vs $0.20 per 1M) and has a 1M-token context window versus 922K.

Prices from LiteLLM's price fileChecked October 21, 2026

Gemini 3.8 Flash vs GPT-5.6 Luna side by side

Headline prices in US dollars per 1M tokens: each model's own lab where it sells it, otherwise its cheapest provider. Source: LiteLLM model price file, as of October 21, 2026.
	Gemini 3.8 Flash	GPT-5.6 Luna
Input, per 1M tokens	$0.75	$0.20
Output, per 1M tokens	$3.75	$1.20
Cache read, per 1M tokens	$0.075	$0.02
Cache write, per 1M tokens	–	$0.25
Context window	1,048,576 tokens	922,000 tokens
Max output	65,536 tokens	128,000 tokens
Image input	Yes	Yes
Tool calling	Yes	Yes
Structured output (JSON)	Yes	Yes
Prompt caching	Yes	Yes
Reasoning	Yes	Yes
Providers on LiteLLM	5	9
Price shown is from	Google AI Studio	OpenAI
Added to LiteLLM	September 2, 2026	July 9, 2026

Cheapest provider for each

Gemini 3.8 Flash: Google AI Studio at $0.75 input and $3.75 output per 1M tokens (gemini/gemini-3.8-flash)
GPT-5.6 Luna: OpenAI at $0.20 input and $1.20 output per 1M tokens (gpt-5.6-luna)

Benchmark scores

From the Epoch AI Benchmarking Hub (CC BY 4.0), data as of September 2, 2026. Some results were run by Epoch and others collected by Epoch from each benchmark's own leaderboard, linked in the first column. Each model's best reported reasoning setting is shown in brackets. Higher is better. Only benchmarks with a score for both models are shown.
Benchmark	Gemini 3.8 Flash	GPT-5.6 Luna
Overall
Epoch Capabilities Index	157.4	156.5
Coding and agents
FrontierCode	41.2% (medium)	39.8%
APEX-Agents	64.3%	43.0%
Reasoning and knowledge
GPQA Diamond	95.4% (high)	91.6% (max)
ARC-AGI-2	89.2% (high)	59.5% (max)
SimpleQA Verified	69.7% (high)	41.0% (max)
Math
FrontierMath (tiers 1-3)	68.4% (high)	82.1% (max)
FrontierMath (tier 4)	22.0% (high)	61.0% (max)
OTIS Mock AIME 2024-2025	98.9% (high)	98.3% (max)

When to pick which

Pick Gemini 3.8 Flash for

Larger context window: 1,048,576 vs 922,000 tokens.

Pick GPT-5.6 Luna for

Costs 73% less per input token: $0.20 vs $0.75 per 1M.
Returns up to 128,000 tokens per response, vs 65,536.

From differences in the data above only; where the data is equal, no reason is given.

Call Gemini 3.8 Flash or GPT-5.6 Luna with LiteLLM

Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.

Python SDK

from litellm import completion

messages = [{"role": "user", "content": "Hello!"}]

# Gemini 3.8 Flash
response = completion(model="gemini/gemini-3.8-flash", messages=messages)

# GPT-5.6 Luna
response = completion(model="gpt-5.6-luna", messages=messages)

# Gemini 3.8 Flash, falling back to GPT-5.6 Luna if the call fails
response = completion(model="gemini/gemini-3.8-flash", messages=messages, fallbacks=["gpt-5.6-luna"])

FAQ

Which is cheaper, Gemini 3.8 Flash or GPT-5.6 Luna?

GPT-5.6 Luna is cheaper at 3 input tokens per output token: $0.45 per 1M tokens blended ($0.20 input, $1.20 output), versus $1.50 ($0.75 and $3.75) for Gemini 3.8 Flash, as of October 21, 2026.

Which has the larger context window, Gemini 3.8 Flash or GPT-5.6 Luna?

Gemini 3.8 Flash has the larger context window: 1,048,576 tokens, versus 922,000 for GPT-5.6 Luna.

Can I switch from Gemini 3.8 Flash to GPT-5.6 Luna without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "gemini/gemini-3.8-flash" to "gpt-5.6-luna", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.