AI model comparison

Ling 3.0 Flash vs Gemma 4 31B

Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.

inclusionai logo

inclusionAI

Ling 3.0 Flash

*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*.

Input / 1M
$0.02
Output / 1M
$0.06
Context
262K

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output.

Input / 1M
$0.09
Output / 1M
$0.34
Context
262K

At a glance

Quick verdict

How the two models stack up on the things people ask about most.

Lower price

inclusionai logo

Ling 3.0 Flash

4.8x cheaper for a typical chat

Higher intelligence score

inclusionai logo

Ling 3.0 Flash

20.1 vs 14.7 on Artificial Analysis

Larger context window

Tie

262K vs 262K tokens

Newer release

inclusionai logo

Ling 3.0 Flash

Released July 23, 2026

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

inclusionai logoLing 3.0 Flash20.1
google logoGemma 4 31B14.7

Coding index

inclusionai logoLing 3.0 Flash50.6
google logoGemma 4 31B43.4

Agentic index

inclusionai logoLing 3.0 Flash19.3
google logoGemma 4 31B4.2

Pricing

Ling 3.0 Flash vs Gemma 4 31B API pricing

Per-token API rates. Cheaper option highlighted.

Metricinclusionai logoLing 3.0 Flashgoogle logoGemma 4 31B
Input tokensPer 1M tokens$0.02$0.09
Output tokensPer 1M tokens$0.06$0.34
Cached input (read)Per 1M tokens$0.00$0.05
Cache writePer 1M tokensNot availableNot available

What it costs in practice

Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.

Chat message

2K in, 500 out

inclusionai logoLing 3.0 Flash$0.07
google logoGemma 4 31B$0.35

Coding task

30K in, 4K out

inclusionai logoLing 3.0 Flash$0.88$0.38 cached
google logoGemma 4 31B$4.06$2.86 cached

Long document summary

150K in, 2K out

inclusionai logoLing 3.0 Flash$3.28$0.76 cached
google logoGemma 4 31B$14.18$8.18 cached

Specs

Context window and capabilities

How much each model can read, how much it can write, and what it accepts as input.

Metricinclusionai logoLing 3.0 Flashgoogle logoGemma 4 31B
Context window262K tokens262K tokens
Max output33K tokens16K tokens
Input typesTextImage, Text, Video
Output typesTextText
Reasoning effort levelsNot availableNot available
Default reasoning effortNot availableNot available
Release dateJuly 23, 2026April 2, 2026

Features

Supported features

API features available for each model.

Metricinclusionai logoLing 3.0 Flashgoogle logoGemma 4 31B
Tool callingSupportedSupported
Structured outputsNot supportedSupported
JSON modeSupportedSupported
ReasoningSupportedSupported
TemperatureSupportedSupported
Stop sequencesSupportedSupported
Deterministic seedSupportedSupported
Verbosity controlNot supportedNot supported

Our take

Ling 3.0 Flash is 4.8x cheaper for a typical chat. Ling 3.0 Flash scores higher on the Artificial Analysis Intelligence Index (20.1 vs 14.7). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.

FAQ

Frequently asked questions

Is Ling 3.0 Flash or Gemma 4 31B cheaper?

Ling 3.0 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). Ling 3.0 Flash costs $0.02 per 1M input tokens and $0.06 per 1M output tokens, while Gemma 4 31B costs $0.09 per 1M input tokens and $0.34 per 1M output tokens.

Which has a bigger context window, Ling 3.0 Flash or Gemma 4 31B?

Ling 3.0 Flash supports up to 262K tokens of context, compared with 262K for Gemma 4 31B.

Is Ling 3.0 Flash smarter than Gemma 4 31B?

On the Artificial Analysis Intelligence Index, Ling 3.0 Flash scores 20.1 and Gemma 4 31B scores 14.7, putting Ling 3.0 Flash ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.

Can I use Ling 3.0 Flash and Gemma 4 31B at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Ling 3.0 Flash and Gemma 4 31B answer side by side and keep the better response.

inclusionai logogoogle logo

Why choose? Ask both.

Send one prompt to Ling 3.0 Flash and Gemma 4 31B at the same time. Compare the answers side by side and keep the best one.