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Precision Benchmarks

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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  3. Meta: Muse Glimmer 30B vs Yi-Large

Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Meta: Muse Glimmer 30B vs Yi-Large benchmark

In this head-to-head showdown, Yi-Large is more budget-friendly at $0.3/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Choose Meta: Muse Glimmer 30B if your priority is peak reasoning, complex code generation, and top preference Elo. Choose Yi-Large if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
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Executive Verdict Summary

Yi-Large holds empirical advantage (2 of 3 metrics)

Coding / SWESWE-bench
Yi-LargeTop code solve rate
ReasoningGPQA / Live
Yi-LargeTop logical accuracy
Best Value$/1M Tok
Yi-LargeLowest API billing cost
Speed / TokTok/Sec
Yi-LargeFastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Meta: Muse Glimmer 30B (1)Yi-Large (2)
Meta: Muse Glimmer 30B
1 of 3 Wins
✓Context window
Yi-Large
2 of 3 Wins
✓Input price✓Output price
Meta
Leads 1 of 3
Meta: Muse Glimmer 30B

Auto-discovered from OpenRouter (meta/muse-glimmer-30b). Preview until a second source matches.

In: $0.35 · Out: $1.5/1M
01.AI
Leads 2 of 3
Yi-Large

01.AI full-scale dense model for complex instruction following.

Elo 1,430In: $0.3 · Out: $0.3/1M
Top Rival Showdowns for Meta: Muse Glimmer 30B
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek V4 Pro
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderYi-Large Wins

Yi-Large

$0.3 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect
0–100 %ile

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Meta: Muse Glimmer 30B (1)vsYi-Large (9)
Meta: Muse Glimmer 30B: 1W (10%)Overall: Yi-LargeYi-Large: 9W (90%)
← Meta: Muse Glimmer 30BYi-Large →
🏆Yi-Large Leads(5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Benchmark
Meta: Muse Glimmer 30BvsYi-Large
Preference Elo
—vs1,430
Coding Elo
—vs1,410
SWE-bench
—vs53.8%
LiveBench
—vs60.5%
GPQA Diamond
—vs72.4%
Meta: Muse Glimmer 30B: 0WYi-Large: 5W
🏆Yi-Large Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Meta: Muse Glimmer 30BvsYi-Large
Output speed
—vs90 tok/s
Time to first token
—vs220 ms
Meta: Muse Glimmer 30B: 0WYi-Large: 2W
🏆Yi-Large Leads(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Meta: Muse Glimmer 30BvsYi-Large
Output price
$1.5/1Mvs$0.3/1M+$1.2/1M
Input price
$0.35/1Mvs$0.3/1M+$0.05/1M
Context window
131kvs33k+98k
Meta: Muse Glimmer 30B: 1WYi-Large: 2W

Side-by-Side Benchmark Matrix

Meta: Muse Glimmer 30BYi-Large
Preference Elo
Meta: Muse Glimmer 30B—
Yi-Large1,430
Coding Elo
Meta: Muse Glimmer 30B—
Yi-Large1,410
LiveBench
Meta: Muse Glimmer 30B—
Yi-Large60.5%
SWE-bench
Meta: Muse Glimmer 30B—
Yi-Large53.8%
GPQA Diamond
Meta: Muse Glimmer 30B—
Yi-Large72.4%
Time to first token
Meta: Muse Glimmer 30B—
Yi-Large220 ms
Output speed
Meta: Muse Glimmer 30B—
Yi-Large90 tok/s
Input priceYi-Large +$0.05/1M
Meta: Muse Glimmer 30B$0.35/1M
Yi-Large$0.3/1M
Output priceYi-Large +$1.2/1M
Meta: Muse Glimmer 30B$1.5/1M
Yi-Large$0.3/1M
Context windowMeta: Muse Glimmer 30B +98k
Meta: Muse Glimmer 30B131k
Yi-Large33k
BenchmarkMeta: Muse Glimmer 30BYi-LargeAdvantage Delta
Preference Elo—
1,430
lmarena · Aug 17, 2026
—
Coding Elo—
1,410
lmarena · Aug 17, 2026
—
LiveBench—
60.5%
livebench · Aug 17, 2026
—
SWE-bench—
53.8%
swebench · Aug 17, 2026
—
GPQA Diamond—
72.4%
seed-bootstrap · Aug 1, 2026
—
Time to first token—
220 ms
seed-bootstrap · Aug 1, 2026
—
Output speed—
90 tok/s
seed-bootstrap · Aug 1, 2026
—
Input price
$0.35/1M
openrouter · Aug 17, 2026
$0.3/1M
seed-bootstrap · Aug 1, 2026
+$0.05/1M
Output price
$1.5/1M
openrouter · Aug 17, 2026
$0.3/1M
seed-bootstrap · Aug 1, 2026
+$1.2/1M
Context window
131k
openrouter · Aug 17, 2026
33k
seed-bootstrap · Aug 1, 2026
+98k

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save 57% with Yi-Large
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Meta: Muse Glimmer 30B$34.75 / mo
In: $12.25Out: $22.5
Yi-Large$15.00 / mo
In: $10.5Out: $4.5
Estimated Cost Delta

Yi-Large is estimated to save $19.75/month ($237/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Yi-Large:Pick Yi-Large when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatYi-Large

Lower output list price ($0.3/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMeta: Muse Glimmer 30B

Larger window (131k).

Screenshots / visionYi-Large

Yi-Large is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatYi-LargeLower output list price ($0.3/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGMeta: Muse Glimmer 30BLarger window (131k).
Screenshots / visionYi-LargeYi-Large is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Meta

Meta: Muse Glimmer 30B

Elo n/a
SWE-bench—
Speed (tok/s)131k
Input / 1M Tokens$0.35/1M
Output / 1M Tokens$1.5/1M
01.AI

Yi-Large

Elo 1,430
SWE-bench53.8%
Speed (tok/s)90 tok/s
Input / 1M Tokens$0.3/1M
Output / 1M Tokens$0.3/1M

Frequently Asked Questions

Which is better overall, Meta: Muse Glimmer 30B or Yi-Large?
We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Meta: Muse Glimmer 30B or Yi-Large?
SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?
Yi-Large output tokens are $0.3/1M versus $1.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Meta: Muse Glimmer 30B or Yi-Large?
We do not have TTFT for both models.
Which has the larger context window?
Meta: Muse Glimmer 30B accepts 131k tokens versus 33k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?
No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?
Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Meta: Muse Glimmer 30B and Yi-Large Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Meta: Muse Glimmer 30B matchups →|All Yi-Large matchups →
Yi-Large vs Yi-Lightning (next other)Llama 4 Maverick vs Yi-LargeClaude Opus 4.5 vs Yi-LargeClaude Opus 4.6 vs Yi-LargeClaude Sonnet 4.5 vs Yi-LargeGPT-5 vs Yi-Large