Gemma 4 31B vs GLM 5.3 Flash

At a Glance

Compare
Gemma 4 31BGoogle DeepMind
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#29 of 4654.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.4–69.8
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#2 of 44$0.0087 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#1 of 3877.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 68.2–84.9
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.090Openrouter · Sep 22, 2026$0.075Z.ai · Aug 29, 2026
Output priceFrom · USD / 1M tokens$0.34Openrouter · Sep 22, 2026$0.25Z.ai · Aug 29, 2026
Context windowMaximum documented tokens262K1,000K
Model facts checkedSep 3, 2026View model evidence →Sep 2, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
BenchmarkGemma 4 31BGLM-5.3-Flash
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,441.6898% of row best · rating · gemma-4-31b; 95% CI [1434.13929794, 1449.22204224]; votes 5894; rank 641,471.89100% of row best · rating · glm-5.3-flash; 95% CI [1465.37026588, 1478.41920488]; votes 10038; rank 24
LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader1,275.9898% of row best · rating · gemma-4-31b; 95% CI [1269.84273447, 1282.11308989]; votes 35713; rank 331,298.71100% of row best · rating · glm-5.3-flash; 95% CI [1287.06707337, 1310.34654848]; votes 3110; rank 17
Overall ResultCounted from the protocol-matched rows above0 benchmark winsNo overall winner2 benchmark winsNo overall winner

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

Side-by-Side Facts

FieldGemma 4 31BGLM-5.3-Flash
DeveloperGoogle DeepMindZ.ai
FamilyGemma 4Glm 5 3 Flash
ModelGemma 4 31BGLM-5.3-Flash
VersionGemma 4 31BGLM-5.3-Flash
Lifecycleactiveactive
Released2026-03-112026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Video, Document
Output modalitiesTextText
Context window262K1,000K
Total parameters31B320B
Active parametersUnknown18B
Licenseapache-2.0MIT
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessCerebras (Standard), Deepinfra (Standard), Google Gemini (Standard), Openrouter (Standard), Together Ai (Standard)Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolsagents, chat, computer-use, reasoning, structured_outputs, tools, vision

Gemma 4 31B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers5
Canonical IDgoogle/gemma-4-31B-it

GLM 5.3 Flash Capabilities

agentschatcomputer-usereasoningstructured outputstoolsvision
Serving providers4
Canonical IDzai-org/glm-5.3-flash

Primary Evidence

Sources and Freshness

Questions

Gemma 4 31B vs GLM 5.3 Flash FAQs

Is Gemma 4 31B or GLM 5.3 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemma 4 31B and GLM 5.3 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemma 4 31B or GLM 5.3 Flash?+

Gemma 4 31B is $0.090 and GLM 5.3 Flash is $0.075 per million tokens, so GLM 5.3 Flash is cheaper on this metric. Gemma 4 31B is $0.34 and GLM 5.3 Flash is $0.25 per million tokens, so GLM 5.3 Flash is cheaper on this metric.

Which has a larger context window, Gemma 4 31B or GLM 5.3 Flash?+

GLM 5.3 Flash has the larger sourced context window. Gemma 4 31B supports 262K and GLM 5.3 Flash supports 1,000K.

Which performs better in benchmarks, Gemma 4 31B or GLM 5.3 Flash?+

There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.

Can Gemma 4 31B or GLM 5.3 Flash be self-hosted?+

Both models have the same recorded self-hosting status: supported. Gemma 4 31B is open weight; GLM 5.3 Flash is open weight.

Can Gemma 4 31B and GLM 5.3 Flash understand images?+

Gemma 4 31B is documented with image input; GLM 5.3 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemma 4 31B or GLM 5.3 Flash?+

Neither has a larger sourced maximum output. Gemma 4 31B is — and GLM 5.3 Flash is 131K.

Do Gemma 4 31B and GLM 5.3 Flash support reasoning and tool use?+

Gemma 4 31B: reasoning, tool calling, and image input. GLM 5.3 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Gemma 4 31B or GLM 5.3 Flash?+

Gemma 4 31B has 5 sourced provider routes; GLM 5.3 Flash has 4, so Gemma 4 31B has broader tracked availability.

Which offers better value, Gemma 4 31B or GLM 5.3 Flash?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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