MolmoWeb 4B vs GLM 5.3

At a Glance

Compare
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#34 of 44$0.248 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$1.20Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$4.00Deepinfra · Sep 22, 2026
Context windowMaximum documented tokens10K1,000K
Model facts checkedSep 3, 2026View model evidence →Aug 29, 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 →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldMolmoWeb 4BGLM-5.3
DeveloperAi2Z.ai
FamilyMolmowebGlm 5 3
ModelMolmoWeb 4BGLM-5.3
VersionMolmoWeb 4BGLM-5.3
Lifecycleactiveactive
Released2026-03-20Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window10K1,000K
Total parameters4.9BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableNoYes
Self-hostableYesNo
Provider accessUnknownDeepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard)
Capabilitieschat, computer-use, generation, tools, visionagents, chat, reasoning, structured_outputs, tools

MolmoWeb 4B Capabilities

chatcomputer-usegenerationtoolsvision
Serving providers0
Canonical IDallenai/MolmoWeb-4B

GLM 5.3 Capabilities

agentschatreasoningstructured outputstools
Serving providers4
Canonical IDzai-org/glm-5.3

Primary Evidence

Sources and Freshness

Questions

MolmoWeb 4B vs GLM 5.3 FAQs

Is MolmoWeb 4B or GLM 5.3 better for coding?+

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

Which is cheaper, MolmoWeb 4B or GLM 5.3?+

Only GLM 5.3 has a directly sourced input price: $1.20 per million tokens. Only GLM 5.3 has a directly sourced output price: $4.00 per million tokens.

Which has a larger context window, MolmoWeb 4B or GLM 5.3?+

GLM 5.3 has the larger sourced context window. MolmoWeb 4B supports 10K and GLM 5.3 supports 1,000K.

Which performs better in benchmarks, MolmoWeb 4B or GLM 5.3?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can MolmoWeb 4B or GLM 5.3 be self-hosted?+

MolmoWeb 4B is the only model in this pair currently marked as self-hostable. MolmoWeb 4B is open weight; GLM 5.3 is not marked open weight.

Can MolmoWeb 4B and GLM 5.3 understand images?+

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

Which can generate longer answers, MolmoWeb 4B or GLM 5.3?+

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

Do MolmoWeb 4B and GLM 5.3 support reasoning and tool use?+

MolmoWeb 4B: tool calling and image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, MolmoWeb 4B or GLM 5.3?+

MolmoWeb 4B has 0 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.

Which offers better value, MolmoWeb 4B or GLM 5.3?+

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.

Send Feedback