Long documents
Prompts that approach the documented context limit
MiniMax M3
MiniMax M3 has the larger documented context window.
Confidence: documented
MiniMax M3 vs Muse Glimmer 30B
Updated September 24, 2026. Rank says MiniMax M3 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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Decision reading
MiniMax M3 has the higher public score estimate, 54.86 versus 41.73, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 7 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 7
- MiniMax M3 only
- 20
- Muse Glimmer 30B only
- 7
- Like-for-like categories
- 0 / 8
Supported: MiniMax M3 · Estimated: Muse Glimmer 30BHow 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.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Muse Glimmer 30B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Muse Glimmer 30B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedChat 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-ratesCache-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-ratesRepository 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.
39.2MiniMax M336.3Muse Glimmer 30B
Directional only · BenchAlign v5.7
MiniMax M3 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
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.
20 MiniMax M3 only
7 Shared
7 Muse Glimmer 30B only
5 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.
SWE-bench ProCoding
Normalized gap 7.8MiniMax M3:59%Muse Glimmer 30B:51.2%SWE-bench VerifiedCoding
Normalized gap 4.5MiniMax M3:80.5%Muse Glimmer 30B:76%OSWorld-VerifiedAgentic
Normalized gap 4.2MiniMax M3:70.1%Muse Glimmer 30B:65.9%MMMU-ProMultimodal
Normalized gap 4.1MiniMax M3:78.1%Muse Glimmer 30B:74%
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 v5.7 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- MiniMax M3
- 39.9
- Supported · #45/105
- Muse Glimmer 30B
- 27.6
- Estimated · #72/105
- Basis
- BenchAlign v5.7 lane · 9 vs 4 public rows
- Reading
- Directional only
Coding
Directional only- MiniMax M3
- 39.2
- Supported · #59/135
- Muse Glimmer 30B
- 36.3
- Estimated · #69/135
- Basis
- BenchAlign v5.7 lane · 10 vs 4 public rows
- Reading
- Directional only
Multimodal
Directional only- MiniMax M3
- 52.0
- #36/50
- Muse Glimmer 30B
- 46.3
- #42/50
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Directional only
Knowledge
Directional only- MiniMax M3
- 49.3
- Supported · #59/158
- Muse Glimmer 30B
- 43.9
- Estimated · #75/158
- Basis
- BenchAlign v5.7 lane · 2 vs 0 public rows
- Reading
- Directional only
Instruction following
Directional only- MiniMax M3
- 92.4
- #5/124
- Muse Glimmer 30B
- 77.7
- #55/124
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- MiniMax M3
- 79.1
- Unranked · 2 rankable rows
- Muse Glimmer 30B
- 79.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- MiniMax M3
- Not ranked
- Muse Glimmer 30B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiniMax M3
- Not ranked
- Muse Glimmer 30B
- 75.4
- Unranked · 1 rankable row
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
| Category | MiniMax M3 | Muse Glimmer 30B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 39.9Supported · #45/105 | 27.6Estimated · #72/105 | Directional onlyBenchAlign v5.7 lane · 9 vs 4 public rows | Directional only |
| Coding | 39.2Supported · #59/135 | 36.3Estimated · #69/135 | Directional onlyBenchAlign v5.7 lane · 10 vs 4 public rows | Directional only |
| Multimodal | 52.0#36/50 | 46.3#42/50 | Directional onlyProvisional lane · 2 vs 2 weighted rows | Directional only |
| Knowledge | 49.3Supported · #59/158 | 43.9Estimated · #75/158 | Directional onlyBenchAlign v5.7 lane · 2 vs 0 public rows | Directional only |
| Instruction following | 92.4#5/124 | 77.7#55/124 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Reasoning | 79.1Unranked · 2 rankable rows | 79.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 75.4Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) 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
- MiniMax M3
- $0.0009
- 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
- MiniMax M3
- $0.0186
- 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
- MiniMax M3
- $0.03
- 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.
SpecificationMiniMax M3Muse Glimmer 30B
Context window
Maximum documented context; output-token limits may be lower.
MiniMax M3
1M
Muse Glimmer 30B
131K
API model ID
MiniMax M3
Not sourced
Muse Glimmer 30B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiniMax M3
$0.06 per 1M cached input tokens
Muse Glimmer 30B
No comparable hosted API rate
Documented inputs
MiniMax M3
Not sourced
Muse Glimmer 30B
Not sourced
Documented outputs
MiniMax M3
Not sourced
Muse Glimmer 30B
Not sourced
Provider availability
MiniMax M3
Not sourced
Muse Glimmer 30B
Not sourced
Reasoning profile
MiniMax M3
Non-Reasoning
Muse Glimmer 30B
Reasoning
Weight access
MiniMax M3
Open Weight
Muse Glimmer 30B
Open Weight
License
MiniMax M3
Open Weight
Muse Glimmer 30B
Open Weight
Release date
MiniMax M3
2026-06-01
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
- MiniMax M3 has the higher public score estimate, 54.86 versus 41.73, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- MiniMax M3 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, MiniMax M3 or Muse Glimmer 30B?
MiniMax M3 has the higher public score estimate, 54.86 versus 41.73, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, MiniMax M3 or Muse Glimmer 30B?
MiniMax M3 scores higher for coding on the public lane, 39.2 to 36.3. Muse Glimmer 30B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, MiniMax M3 or Muse Glimmer 30B?
MiniMax M3 scores higher for agentic tasks on the public lane, 39.9 to 27.6. Muse Glimmer 30B is 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, MiniMax M3 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, MiniMax M3 or Muse Glimmer 30B?
MiniMax M3 has the larger documented context window: 1M, compared with 131K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence34 rows
Agentic
Terminal-Bench 2.1
MiniMax M366.0%SourceMuse Glimmer 30B—Not directly comparable
BrowseComp
MiniMax M383.5%SourceMuse Glimmer 30B—Not directly comparable
OSWorld-Verified
MiniMax M370.1%SourceMuse Glimmer 30B65.9%SourceMiniMax M3 leads this result
MCP Atlas
MiniMax M374.2%SourceMuse Glimmer 30B75.5%SourceMuse Glimmer 30B leads this result
Claw-Eval
MiniMax M374.5%SourceMuse Glimmer 30B—Not directly comparable
BankerToolBench
MiniMax M376.1%SourceMuse Glimmer 30B—Not directly comparable
ResearchClawBench
MiniMax M319.8%SourceMuse Glimmer 30B—Not directly comparable
OSWorld 2.0
MiniMax M34.6%SourceMuse Glimmer 30B—Not directly comparable
Terminal-Bench 2.1 (Vals)
MiniMax M353.6%SourceMuse Glimmer 30B—Not directly comparable
DeepSearchQA
MiniMax M3—Muse Glimmer 30B74.6%SourceNot directly comparable
skillsBench
MiniMax M3—Muse Glimmer 30B44.3%SourceNot directly comparable
Coding
SWE-bench Verified
MiniMax M380.5%SourceMuse Glimmer 30B76%SourceMiniMax M3 leads this result
SWE-bench Pro
MiniMax M359%SourceMuse Glimmer 30B51.2%SourceMiniMax M3 leads this result
Terminal-Bench 2.1
MiniMax M366.0%SourceMuse Glimmer 30B51.7%SourceMiniMax M3 leads this result
NL2Repo
MiniMax M342.1%SourceMuse Glimmer 30B—Not directly comparable
VIBE V2
MiniMax M350.1%SourceMuse Glimmer 30B—Not directly comparable
SVG-Bench
MiniMax M363.7%SourceMuse Glimmer 30B—Not directly comparable
KernelBench Hard
MiniMax M328.8%SourceMuse Glimmer 30B—Not directly comparable
OpenHarmony Bench
MiniMax M348.4%SourceMuse Glimmer 30B—Not directly comparable
LiveCodeBench (Vals)
MiniMax M382.2%SourceMuse Glimmer 30B—Not directly comparable
SWE-bench (Vals)
MiniMax M375.0%SourceMuse Glimmer 30B—Not directly comparable
SciCode
MiniMax M3—Muse Glimmer 30B43.6%SourceNot directly comparable
Multimodal
OfficeQA Pro
MiniMax M345.1%SourceMuse Glimmer 30B—Not directly comparable
OmniDocBench 1.5
MiniMax M391.6%SourceMuse Glimmer 30B75.8%SourceMiniMax M3 leads this result
MMMU-Pro
MiniMax M378.1%SourceMuse Glimmer 30B74%SourceMiniMax M3 leads this result
VideoMMMU
MiniMax M384.6%SourceMuse Glimmer 30B—Not directly comparable
Video-MME (with subtitle)
MiniMax M385.4%SourceMuse Glimmer 30B—Not directly comparable
CharXiv
MiniMax M3—Muse Glimmer 30B78.8%SourceNot directly comparable
ScreenSpot Pro
MiniMax M3—Muse Glimmer 30B75.4%SourceNot directly comparable
Knowledge
Instruction following
IFBench
MiniMax M3—Muse Glimmer 30B77%SourceNot directly comparable
Math
34 public results · 7 shared
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Last updated September 24, 2026