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Gemini 3.5 Flash Lite vs Morph V3 Fast

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 3.5 Flash Lite and Morph V3 Fast are priced within ~10% of each other.

Morph V3 Fast 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.

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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

morph

Morph V3 Fast

Blended / 1M
$0.900
Context
82K
Released
Jul 7, 2025
Overall score
Not evaluated

Specs and pricing

MetricGemini 3.5 Flash LiteMorph V3 Fast
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$0.900
Input price / 1M$0.300win$0.800
Output price / 1M$2.50$1.20win
Cached input / 1M

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

$0.030
Context window1.0Mwin82K
Max output tokens66Kwin38K

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, Morph V3 Fast 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 LiteMorph V3 Fast
Support chatbot

1.2K in / 400 out × 200K requests

$252.56/mo$288.00/mo
RAG assistant

8K in / 600 out × 100K requests

$282.00/mo$712.00/mo
Coding agent

40K in / 4K out × 20K requests

$288.80/mo$736.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$474.00/mo$890.00/mo
Bulk classification

500 in / 20 out × 5M requests

$865.00/mo$2,120/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 82K.

Gemini 3.5 Flash Lite vs Morph V3 Fast FAQ

Which is better, Gemini 3.5 Flash Lite or Morph V3 Fast?

Gemini 3.5 Flash Lite and Morph V3 Fast are priced within ~10% of each other. Morph V3 Fast 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 Morph V3 Fast?

They cost about the same. Both land near $0.850 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does Gemini 3.5 Flash Lite or Morph V3 Fast have a bigger context window?

Gemini 3.5 Flash Lite has the larger context window: 1.0M for Gemini 3.5 Flash Lite against 82K for Morph V3 Fast. 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 Morph V3 Fast support prompt caching?

Gemini 3.5 Flash Lite publishes a cached-input rate of $0.030 per million tokens against a full input rate of $0.300. The catalogue lists no separate cached rate for Morph V3 Fast, which means the provider does not price it separately here — not that caching is unavailable.

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.