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GPT-6.1 Terra vs Muse Glimmer 30B

Updated October 26, 2026. Rank says GPT-6.1 Terra is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

GPT-6.1 Terra has the higher public point estimate, 75.87 versus 41.24. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
OpenAI logo
GPT-6.1 Terra

OpenAI

75.87/100

Estimated · Public rank #10

Conditional range 61.5–90.2

Model B
Meta logo
Muse Glimmer 30B

Meta

41.24/100

Estimated · Public rank #133

Conditional range 26.9–55.6

Shared results
1
GPT-6.1 Terra only
9
Muse Glimmer 30B only
13
Like-for-like categories
0 / 8
Estimated: GPT-6.1 Terra and Muse Glimmer 30B. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    GPT-6.1 Terra

    GPT-6.1 Terra has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT-6.1 Terra is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    GPT-6.1 Terra and Muse Glimmer 30B are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Muse Glimmer 30B does not fit this workload in one request. Muse Glimmer 30B has no comparable published API token rate.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—GPT-6.1 Terra31.0Muse Glimmer 30B

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Directional only
GPT-6.1 Terra
72.4
Estimated · #8/133
Muse Glimmer 30B
25.7
Estimated · #107/133
Basis
BenchAlign v5.8 lane · 4 vs 4 public rows
Reading
Directional only

Multimodal

Directional only
GPT-6.1 Terra
91.6
#4/58
Muse Glimmer 30B
65.2
#45/58
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Directional only

Knowledge

Directional only
GPT-6.1 Terra
74.9
Supported · #12/188
Muse Glimmer 30B
43.2
Estimated · #107/188
Basis
BenchAlign v5.8 lane · 5 vs 0 public rows
Reading
Directional only

Coding

Not comparable
GPT-6.1 Terra
Not ranked
Muse Glimmer 30B
31.0
Estimated · #98/154
Basis
BenchAlign v5.8 lane · 0 vs 4 public rows
Reading
Not comparable

Reasoning

Not comparable
GPT-6.1 Terra
81.8
Unranked · 2 rankable rows
Muse Glimmer 30B
82.2
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
GPT-6.1 Terra
Not ranked
Muse Glimmer 30B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
GPT-6.1 Terra
Not ranked
Muse Glimmer 30B
81.1
#61/155
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
GPT-6.1 Terra
Not ranked
Muse Glimmer 30B
84.6
Unranked · 1 rankable row
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

GPT-6.1 Terra
$0.0035
Fits in one request
Muse Glimmer 30B
Self-hosted; infrastructure cost varies
Fits in one request

Muse Glimmer 30B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-6.1 Terra
$0.065
Fits in one request
Muse Glimmer 30B
Self-hosted; infrastructure cost varies
Fits in one request

Muse Glimmer 30B has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

GPT-6.1 Terra
$0.08
Fits in one request
Muse Glimmer 30B
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable

Muse Glimmer 30B does not fit this workload in one request. Muse Glimmer 30B has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

GPT-6.1 Terra

$0.05 per 1M cached input tokens

OpenAI GPT-6.1 Terra model documentation

Muse Glimmer 30B

No comparable hosted API rate

Reasoning profile

GPT-6.1 Terra

Reasoning

Muse Glimmer 30B

Reasoning

Weight access

GPT-6.1 Terra

Proprietary

Muse Glimmer 30B

Open Weight

License

GPT-6.1 Terra

Proprietary

Muse Glimmer 30B

Open Weight

Release date

GPT-6.1 Terra

2026-10-26

Muse Glimmer 30B

2026-08-10

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
GPT-6.1 Terra has the higher public point estimate, 75.87 versus 41.24. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
GPT-6.1 Terra has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, GPT-6.1 Terra or Muse Glimmer 30B?

GPT-6.1 Terra has the higher public point estimate, 75.87 versus 41.24. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, GPT-6.1 Terra or Muse Glimmer 30B?

GPT-6.1 Terra is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, GPT-6.1 Terra or Muse Glimmer 30B?

GPT-6.1 Terra scores higher for agentic tasks on the public lane, 72.4 to 25.7. GPT-6.1 Terra and Muse Glimmer 30B are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, GPT-6.1 Terra or Muse Glimmer 30B?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, GPT-6.1 Terra or Muse Glimmer 30B?

GPT-6.1 Terra has the larger documented context window: 1.05M, compared with 131K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

GPT-6.1 Terra
API / mo$4,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Muse Glimmer 30B
API / mo$0
Self-host / mo$298
Break-even—
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence23 rows

Agentic

  • Terminal-Bench 4.0

    GPT-6.1 Terra50.30%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    GPT-6.1 Terra58.3%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • Agents' Last Exam

    GPT-6.1 Terra60.0%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • OSWorld 2.1 Offline

    GPT-6.1 Terra74.2%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • MCP Atlas

    GPT-6.1 Terra—
    Muse Glimmer 30B75.5%
    Source

    Not directly comparable

  • DeepSearchQA

    GPT-6.1 Terra—
    Muse Glimmer 30B74.6%
    Source

    Not directly comparable

  • skillsBench

    GPT-6.1 Terra—
    Muse Glimmer 30B44.3%
    Source

    Not directly comparable

  • OSWorld-Verified

    GPT-6.1 Terra—
    Muse Glimmer 30B65.9%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    GPT-6.1 Terra—
    Muse Glimmer 30B51.2%
    Source

    Not directly comparable

  • SWE-bench Verified

    GPT-6.1 Terra—
    Muse Glimmer 30B76%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    GPT-6.1 Terra—
    Muse Glimmer 30B51.7%
    Source

    Not directly comparable

  • SciCode

    GPT-6.1 Terra—
    Muse Glimmer 30B43.6%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    GPT-6.1 Terra85.5%
    Source
    Muse Glimmer 30B74%
    Source

    GPT-6.1 Terra leads this result

  • CharXiv

    GPT-6.1 Terra—
    Muse Glimmer 30B78.8%
    Source

    Not directly comparable

  • ScreenSpot Pro

    GPT-6.1 Terra—
    Muse Glimmer 30B75.4%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    GPT-6.1 Terra—
    Muse Glimmer 30B75.8%
    Source

    Not directly comparable

Knowledge

  • HealthBench (raw)

    GPT-6.1 Terra51.1%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • HealthBench (length-adjusted)

    GPT-6.1 Terra55.1%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • HealthBench Professional

    GPT-6.1 Terra62.7%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • HealthBench Professional (raw)

    GPT-6.1 Terra64.2%
    Source
    Muse Glimmer 30B—

    Not directly comparable

  • HealthBench Hard

    GPT-6.1 Terra31.4%
    Source
    Muse Glimmer 30B—

    Not directly comparable

Instruction following

  • IFBench

    GPT-6.1 Terra—
    Muse Glimmer 30B77%
    Source

    Not directly comparable

Math

  • AIME26

    GPT-6.1 Terra—
    Muse Glimmer 30B94.7%
    Source

    Not directly comparable

23 public results · 1 shared

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Last updated October 26, 2026