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Gemini 3.8 Flash vs Qwen3.8 Flash

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Gemini 3.8 Flash scores higher, Qwen3.8 Flash costs less — it depends on your workload.

Gemini 3.8 Flash is ahead by 20.4 points overall, and Qwen3.8 Flash lists 6.5× cheaper per blended million tokens. Whether 20.4 points is worth that depends on how much a wrong answer costs you. Qwen3.8 Flash also leads on measured cost per point of capability, at $0.2009 per point.

google

Gemini 3.8 Flash

Blended / 1M
$1.50
Context
1.0M
Released
Sep 2, 2026
Overall score
67.3
reasoningtool callingimage inputvideo inputfile inputaudio inputprompt caching

qwen

Qwen3.8 Flash

Blended / 1M
$0.230
Context
1M
Released
Aug 26, 2026
Overall score
47.0
reasoningtool callingimage inputvideo inputprompt caching

Specs and pricing

MetricGemini 3.8 FlashQwen3.8 Flash
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

67.3win47.0
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.7520$0.2009win
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$1.50$0.230win
Input price / 1M$0.750$0.150win
Output price / 1M$3.75$0.470win
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.075$0.016win
Context window1.0M1M
Max output tokens66K131Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemini 3.8 Flash on top, Qwen3.8 Flash below, both out of 100.

Coding
82.2
53.5
Reasoning
89.3
87.4
Data analysis
54.0
74.2

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadGemini 3.8 FlashQwen3.8 Flash
Support chatbot

1.2K in / 400 out × 200K requests

$431.40/mo$63.95/mo
RAG assistant

8K in / 600 out × 100K requests

$555.00/mo$94.60/mo
Coding agent

40K in / 4K out × 20K requests

$522.00/mo$82.56/mo
Document extraction

20K in / 1.5K out × 50K requests

$997.50/mo$178.55/mo
Bulk classification

500 in / 20 out × 5M requests

$1,912/mo$355.00/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

Qwen3.8 Flash

Lowest measured cost per point of capability at $0.2009 per point — the gap compounds with every request.

Quality matters more than the bill

Gemini 3.8 Flash

Highest overall LiveBench score of the two at 67.3.

The workload is coding or agentic work

Gemini 3.8 Flash

Leads on coding — 82.2 against 53.5.

Gemini 3.8 Flash vs Qwen3.8 Flash FAQ

Which is better, Gemini 3.8 Flash or Qwen3.8 Flash?

Gemini 3.8 Flash scores higher, Qwen3.8 Flash costs less — it depends on your workload. Gemini 3.8 Flash is ahead by 20.4 points overall, and Qwen3.8 Flash lists 6.5× cheaper per blended million tokens. Whether 20.4 points is worth that depends on how much a wrong answer costs you. Qwen3.8 Flash also leads on measured cost per point of capability, at $0.2009 per point.

Is Gemini 3.8 Flash cheaper than Qwen3.8 Flash?

Qwen3.8 Flash is cheaper. On a 3:1 input:output blend, Gemini 3.8 Flash lists at $1.50 per million tokens and Qwen3.8 Flash at $0.230 — Qwen3.8 Flash is 6.5× cheaper. Input and output are priced separately — Gemini 3.8 Flash charges $0.750 in and $3.75 out, Qwen3.8 Flash charges $0.150 and $0.470 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Gemini 3.8 Flash vs Qwen3.8 Flash: which scores higher on benchmarks?

Gemini 3.8 Flash scores 67.3 and Qwen3.8 Flash scores 47.0 overall on LiveBench, the mean of its seven categories. That is a 20.4-point lead for Gemini 3.8 Flash. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.

Which gives better value for money, Gemini 3.8 Flash or Qwen3.8 Flash?

Qwen3.8 Flash. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Gemini 3.8 Flash works out at $0.7520 per point and Qwen3.8 Flash at $0.2009.

Does Gemini 3.8 Flash or Qwen3.8 Flash have a bigger context window?

They are effectively the same — 1.0M for Gemini 3.8 Flash and 1M for Qwen3.8 Flash.

Do Gemini 3.8 Flash and Qwen3.8 Flash support prompt caching?

Both publish a cached-input rate: $0.075 per million for Gemini 3.8 Flash and $0.016 for Qwen3.8 Flash, against full input rates of $0.750 and $0.150. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • Scores — LiveBench release 2026-09-02, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.