// head_to_head

Gemini 3.5 Flash Lite vs Qwen3 VL 235B A22B Instruct

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

Qwen3 VL 235B A22B Instruct is the cheaper of the two; neither can be ranked on quality here.

Qwen3 VL 235B A22B Instruct does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

google

Gemini 3.5 Flash Lite

Blended / 1M
$0.850
Context
1.0M
Released
Jul 21, 2026
Overall score
63.9
reasoningtool callingimage inputvideo inputfile inputaudio inputprompt caching

qwen

Qwen3 VL 235B A22B Instruct

Blended / 1M
$0.632
Context
262K
Released
Sep 23, 2025
Overall score
Not evaluated
tool callingimage inputprompt caching

Specs and pricing

MetricGemini 3.5 Flash LiteQwen3 VL 235B A22B Instruct
LiveBench overall

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

63.9
Cost per point

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

$0.0379
Blended price / 1M

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

$0.850$0.632win
Input price / 1M$0.300$0.210win
Output price / 1M$2.50$1.90win
Cached input / 1M

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

$0.030win$0.100
Context window1.0Mwin262K
Max output tokens66Kwin33K

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemini 3.5 Flash Lite on top, Qwen3 VL 235B A22B Instruct below, both out of 100.

Agentic coding
45.3
Coding
76.1
Reasoning
60.2
Mathematics
73.7
Data analysis
53.2
Language
71.8
Instruction following
67.2

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 3.5 Flash LiteQwen3 VL 235B A22B Instruct
Support chatbot

1.2K in / 400 out × 200K requests

$252.56/mo$194.48/mo
RAG assistant

8K in / 600 out × 100K requests

$282.00/mo$238.00/mo
Coding agent

40K in / 4K out × 20K requests

$288.80/mo$258.40/mo
Document extraction

20K in / 1.5K out × 50K requests

$474.00/mo$347.00/mo
Bulk classification

500 in / 20 out × 5M requests

$865.00/mo$660.00/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Gemini 3.5 Flash Lite

Wider context window — 1.0M against 262K.

You are cost-constrained

Qwen3 VL 235B A22B Instruct

Cheaper on blended list price at $0.632 per million tokens.

Gemini 3.5 Flash Lite vs Qwen3 VL 235B A22B Instruct FAQ

Which is better, Gemini 3.5 Flash Lite or Qwen3 VL 235B A22B Instruct?

Qwen3 VL 235B A22B Instruct is the cheaper of the two; neither can be ranked on quality here. Qwen3 VL 235B A22B Instruct does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Gemini 3.5 Flash Lite cheaper than Qwen3 VL 235B A22B Instruct?

Qwen3 VL 235B A22B Instruct is cheaper. On a 3:1 input:output blend, Gemini 3.5 Flash Lite lists at $0.850 per million tokens and Qwen3 VL 235B A22B Instruct at $0.632 — Qwen3 VL 235B A22B Instruct is 34% cheaper. Input and output are priced separately — Gemini 3.5 Flash Lite charges $0.300 in and $2.50 out, Qwen3 VL 235B A22B Instruct charges $0.210 and $1.90 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Gemini 3.5 Flash Lite or Qwen3 VL 235B A22B Instruct have a bigger context window?

Gemini 3.5 Flash Lite has the larger context window: 1.0M for Gemini 3.5 Flash Lite against 262K for Qwen3 VL 235B A22B Instruct. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Gemini 3.5 Flash Lite and Qwen3 VL 235B A22B Instruct support prompt caching?

Both publish a cached-input rate: $0.030 per million for Gemini 3.5 Flash Lite and $0.100 for Qwen3 VL 235B A22B Instruct, against full input rates of $0.300 and $0.210. 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.
  • ScoresLiveBench release 2026-06-25, 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.