NVIDIA Nemotron 3 Super 120B A12B Base BF16 vs GLM OCR

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens1,049K131K
Model facts checkedAug 28, 2026View model evidence →Aug 28, 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

FieldNVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16GLM-OCR
DeveloperNVIDIAZ.ai
FamilyNvidia Nemotron 3 Super 120b A12b Base Bf16Glm OCR
ModelNVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16GLM-OCR
VersionNVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16GLM-OCR
Lifecycleactiveactive
Released2026-03-04Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window1,049K131K
Total parameters123.6B1.3B
Active parameters12BUnknown
Licenseothermit
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownTogether Ai (Standard)
Capabilitiesgenerationchat, generation, tools

NVIDIA Nemotron 3 Super 120B A12B Base BF16 Capabilities

generation
Serving providers0
Canonical IDnvidia/NVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16

GLM OCR Capabilities

chatgenerationtools
Serving providers1
Canonical IDzai-org/GLM-OCR

Primary Evidence

Sources and Freshness

Questions

NVIDIA Nemotron 3 Super 120B A12B Base BF16 vs GLM OCR FAQs

Is NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both NVIDIA Nemotron 3 Super 120B A12B Base BF16 and GLM OCR, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

NVIDIA Nemotron 3 Super 120B A12B Base BF16 has the larger sourced context window. NVIDIA Nemotron 3 Super 120B A12B Base BF16 supports 1,049K and GLM OCR supports 131K.

Which performs better in benchmarks, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

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

Can NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR be self-hosted?+

Both models have the same recorded self-hosting status: supported. NVIDIA Nemotron 3 Super 120B A12B Base BF16 is open weight; GLM OCR is open weight.

Can NVIDIA Nemotron 3 Super 120B A12B Base BF16 and GLM OCR understand images?+

NVIDIA Nemotron 3 Super 120B A12B Base BF16 is not documented with image input; GLM OCR is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

Neither has a larger sourced maximum output. NVIDIA Nemotron 3 Super 120B A12B Base BF16 is — and GLM OCR is —.

Do NVIDIA Nemotron 3 Super 120B A12B Base BF16 and GLM OCR support reasoning and tool use?+

NVIDIA Nemotron 3 Super 120B A12B Base BF16: none of these features are definitively sourced. GLM OCR: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

NVIDIA Nemotron 3 Super 120B A12B Base BF16 has 0 sourced provider routes; GLM OCR has 1, so GLM OCR has broader tracked availability.

Which offers better value, NVIDIA Nemotron 3 Super 120B A12B Base BF16 or GLM OCR?+

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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