Gemini 4 Carbon vs Qwen3.8 Max

As of November 10, 2026, Gemini 4 Carbon and Qwen3.8 Max cost the same per input token ($2.00 per 1M), but Gemini 4 Carbon costs 67% more per output token ($10.00 vs $6.00) and has a 1M-token context window versus 992K.

Prices from LiteLLM's price fileChecked November 10, 2026

Gemini 4 Carbon vs Qwen3.8 Max 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 November 10, 2026.
	Gemini 4 Carbon	Qwen3.8 Max
Input, per 1M tokens	$2.00	$2.00
Output, per 1M tokens	$10.00	$6.00
Cache read, per 1M tokens	$0.10	$0.25
Cache write, per 1M tokens	–	–
Context window	1,048,576 tokens	991,808 tokens
Max output	1,048,576 tokens	131,072 tokens
Image input	Yes	Yes
Tool calling	Yes	Yes
Structured output (JSON)	Yes	Yes
Prompt caching	Yes	Yes
Reasoning	Yes	Yes
Providers on LiteLLM	2	12
Price shown is from	Google AI Studio	Alibaba Cloud Model Studio
Added to LiteLLM	November 10, 2026	August 7, 2026

Cheapest provider for each

Gemini 4 Carbon: Google AI Studio at $2.00 input and $10.00 output per 1M tokens (gemini/gemini-4-carbon)
Qwen3.8 Max: DeepInfra at $1.65 input and $4.951 output per 1M tokens (deepinfra/Qwen/Qwen3.8-Max)

Benchmark scores

From the Epoch AI Benchmarking Hub (CC BY 4.0), data as of August 27, 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 4 Carbon	Qwen3.8 Max
Coding and agents
FrontierSWE	61.2% (high)	15.8% (xhigh)
APEX-Agents	84.2%	63.3%

When to pick which

Pick Gemini 4 Carbon for

Returns up to 1,048,576 tokens per response, vs 131,072.

Pick Qwen3.8 Max for

Costs 40% less per output token: $6.00 vs $10.00 per 1M.
Available from 12 providers through LiteLLM, vs 2.

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

Call Gemini 4 Carbon or Qwen3.8 Max 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 4 Carbon
response = completion(model="gemini/gemini-4-carbon", messages=messages)

# Qwen3.8 Max
response = completion(model="dashscope/qwen3.8-max", messages=messages)

# Gemini 4 Carbon, falling back to Qwen3.8 Max if the call fails
response = completion(model="gemini/gemini-4-carbon", messages=messages, fallbacks=["dashscope/qwen3.8-max"])

FAQ

Which is cheaper, Gemini 4 Carbon or Qwen3.8 Max?

Qwen3.8 Max is cheaper at 3 input tokens per output token: $3.00 per 1M tokens blended ($2.00 input, $6.00 output), versus $4.00 ($2.00 and $10.00) for Gemini 4 Carbon, as of November 10, 2026.

Which has the larger context window, Gemini 4 Carbon or Qwen3.8 Max?

Gemini 4 Carbon has the larger context window: 1,048,576 tokens, versus 991,808 for Qwen3.8 Max.

Can I switch from Gemini 4 Carbon to Qwen3.8 Max without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "gemini/gemini-4-carbon" to "dashscope/qwen3.8-max", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.