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AI Choice Engine

Model comparison

Base 1 vs Muse Glimmer 30B

Base44 against Meta, compared on context, price, and attributed benchmark results.

Base 1: profile checked October 25, 2026Muse Glimmer 30B: profile checked October 25, 2026Individual provider fields may changeEvidence confidence: Insufficient data — see receipts below

Base44

Base 1

Balanced

vs

Meta

Muse Glimmer 30B

Balanced · Open weights

AI model capability comparison
SpecificationBase 1Muse Glimmer 30B
ProviderBase44Meta
TierBalancedBalanced
Context windowNot verifiedUnverified131K
Max outputNot verifiedUnverifiedNot verifiedUnverified
Input / 1M tokensNot verifiedUnverifiedNot verifiedUnverified
Output / 1M tokensNot verifiedUnverifiedNot verifiedUnverified
WeightsNot verifiedUnverifiedOpen
ParametersNot verifiedUnverified~29.78B total including vision (checkpoint metadata; marketed as 30B)
Reasoning levelsNot verifiedUnverifiedlow, medium, high, xhigh
Modalitiestexttext, image
LicenseNot verifiedUnverifiedApache 2.0
ReleasedJune 29, 2026August 10, 2026

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Pricing tiers

Base 1: Uses Base44 message credits. Model-specific cost is shown under Credits Used per message; no direct token-rate API price is verified.

Muse Glimmer 30B: Apache 2.0 weights, not served by Meta Model API; no first-party token tariff is verified. Self-hosting incurs compute/storage costs. Native config context is 131,072; longer-context support is a publisher claim, not an independently verified maximum.

BalancedRecord checked October 25, 2026

Base 1

Base44's first in-house model is offered in its app-building chat, with the publisher describing it as trained on platform building patterns.

Best for

  • Evaluating app-building prompts within Base44
  • Comparing builder output in an eligible Base44 account

Watch out

The current founder article explicitly says Published June 29, 2026 and 'Today, we announced' Base 1; this establishes the announcement date, not a universal account rollout date. No direct inference endpoint, stable API ID, downloadable checkpoint/licence, exact context/output, parameter count or comparable numeric benchmark is verified. The current manual-selection guide requires Builder or higher and explicitly excludes Base 1 from the effort selector. Per-message Credits Used is authoritative; in-app agent integration-credit prices are a different billing surface. The historical product changelog was not successfully re-fetched, so no broader all-plan availability is asserted.

BalancedOpen weightsRecord checked October 25, 2026

Muse Glimmer 30B

Muse Glimmer 30B is Meta's open-weight smaller Muse model for efficient self-hosting.

Best for

  • Open-weight deployments
  • Single-GPU serving
  • Cost-sensitive

Watch out

Native template reasoning_strength low/medium/high/xhigh defaults high. It supports one tool call per turn, not parallel tool calls; standard serving APIs parse the native ATEM format. BF16 is about 60 GB; published 17 GB/20 GB GGUFs also need a separate 1.4 GB vision projector and optional 1.6 GB draft. Actual hardware fit/speed depends on runtime/context; weight footprint excludes KV cache and overhead. Current config fixes 131,072 positions, while longer-context support remains a publisher claim without a verified ceiling. A separate hard output cap remains unknown. Spark Open’s xhigh default, sparse architecture and parallel tool support must not be inherited.

When the cheaper one wins

One of these rows is missing a verified output price, so this page will not name a cheaper winner. Run the model picker against the actual job instead of guessing.

Run the model picker

Evidence confidence: Insufficient data

How strong and complete the evidence behind this comparison is — not a prediction of which model is better. Hard limitations apply: missing pricing; evidence too sparse.

  • Pricing incomplete — No verified token pricing for Base 1 and Muse Glimmer 30B.
  • 1/5 core specs verified on both sides — Not published for at least one side: context window, max output, parameter count, reasoning levels.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 1 day ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Base 1 · Muse Glimmer 30B

Common questions

Base 1 vs Muse Glimmer 30B

Answered from the verified figures on this page rather than general guidance.

Should I use Base 1 or Muse Glimmer 30B?
Both are classified in our balanced tier; this editorial grouping does not imply equal capability. Base 1 is a candidate for evaluating app-building prompts within base44; Muse Glimmer 30B is a candidate for open-weight deployments. Compare accuracy, tool reliability, latency and cost on representative tasks.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

These two models match on every verified catalog figure — the decision comes down to provider preference, availability, and workload fit rather than published numbers.

Run the model pickerEstimate stack costAll model comparisons

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