Olmo 3.1 32B Instruct vs GLM 5.1

At a Glance

Compare
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$1.05Deepinfra · Sep 23, 2026
Output priceFrom · USD / 1M tokensNot reported$3.50Deepinfra · Sep 23, 2026
Context windowMaximum documented tokens66K203K
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 →
BenchmarkOlmo-3.1-32B-InstructGLM-5.1
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,311.8390% of row best · rating · olmo-3.1-32b-instruct; 95% CI [1305.66595265, 1318.00150818]; votes 11452; rank 2271,462.38100% of row best · rating · glm-5.1; 95% CI [1458.52340519, 1466.22702609]; votes 48901; rank 33
Overall ResultCounted from the protocol-matched rows above0 benchmark winsNo overall winner1 benchmark winNo 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

FieldOlmo-3.1-32B-InstructGLM-5.1
DeveloperAi2Z.ai
FamilyOlmo 3 1 32b InstructGlm 5 1
ModelOlmo-3.1-32B-InstructGLM-5.1
VersionOlmo-3.1-32B-InstructGLM-5.1
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window66K203K
Total parameters32.2B753.9B
Active parametersUnknownUnknown
Licenseapache-2.0mit
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generation, toolschat, generation, reasoning, tools

Olmo 3.1 32B Instruct Capabilities

chatgenerationtools
Serving providers0
Canonical IDallenai/Olmo-3.1-32B-Instruct

GLM 5.1 Capabilities

chatgenerationreasoningtools
Serving providers4
Canonical IDzai-org/GLM-5.1

Primary Evidence

Sources and Freshness

Questions

Olmo 3.1 32B Instruct vs GLM 5.1 FAQs

Is Olmo 3.1 32B Instruct or GLM 5.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3.1 32B Instruct and GLM 5.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Olmo 3.1 32B Instruct or GLM 5.1?+

Only GLM 5.1 has a directly sourced input price: $1.05 per million tokens. Only GLM 5.1 has a directly sourced output price: $3.50 per million tokens.

Which has a larger context window, Olmo 3.1 32B Instruct or GLM 5.1?+

GLM 5.1 has the larger sourced context window. Olmo 3.1 32B Instruct supports 66K and GLM 5.1 supports 203K.

Which performs better in benchmarks, Olmo 3.1 32B Instruct or GLM 5.1?+

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

Can Olmo 3.1 32B Instruct or GLM 5.1 be self-hosted?+

Both models have the same recorded self-hosting status: supported. Olmo 3.1 32B Instruct is open weight; GLM 5.1 is open weight.

Can Olmo 3.1 32B Instruct and GLM 5.1 understand images?+

Olmo 3.1 32B Instruct is not documented with image input; GLM 5.1 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Olmo 3.1 32B Instruct or GLM 5.1?+

Neither has a larger sourced maximum output. Olmo 3.1 32B Instruct is 33K and GLM 5.1 is —.

Do Olmo 3.1 32B Instruct and GLM 5.1 support reasoning and tool use?+

Olmo 3.1 32B Instruct: tool calling. GLM 5.1: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Olmo 3.1 32B Instruct or GLM 5.1?+

Olmo 3.1 32B Instruct has 0 sourced provider routes; GLM 5.1 has 4, so GLM 5.1 has broader tracked availability.

Which offers better value, Olmo 3.1 32B Instruct or GLM 5.1?+

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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