Is GLM 5.3 better than Muse Spark 1.3?

GLM 5.3 (max) and Muse Spark 1.3 (max) are neck and neck on quality (59.0 vs 61.9, within the ±4.5 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.

GLM 5.3 vs Muse Spark 1.3: which is cheaper, and will that change?

Muse Spark 1.3 is cheaper today: $2.00 against $2.15 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is GLM 5.3 or Muse Spark 1.3 better for coding?

They are level in coding (60 vs 61 on the category index). On Arena WebDev, the top shared coding benchmark, it is 1623 for GLM 5.3 against 1656 for Muse Spark 1.3.

Which is faster, GLM 5.3 or Muse Spark 1.3?

Muse Spark 1.3 streams ~2× faster (194 vs 89 output tokens per second, Artificial Analysis 7-day median).

Is GLM 5.3 or Muse Spark 1.3 better for agents and tool use?

Muse Spark 1.3 scores higher in agentic tasks (66 vs 58 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 50.3% for GLM 5.3 against 50.5% for Muse Spark 1.3.

Which is better for long documents?

Muse Spark 1.3 scores higher on long-context benchmarks (66 vs 65). Both take about 1M tokens: GLM 5.3 1,000,000, Muse Spark 1.3 1,048,576.

Which has lower latency?

GLM 5.3 answers first: 23.9 s against 46.3 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.

When was Muse Spark 1.3 released?

Muse Spark 1.3 was released on 2 Sep 2026.

GLM 5.3 vs Muse Spark 1.3

Full profiles: GLM 5.3 (Zhipu AI) and Muse Spark 1.3 (Meta): every benchmark, price and rank.

Updated 1 Nov 2026 · Data from 10 sources

As of 2 Nov 2026, GLM 5.3 and Muse Spark 1.3 are neck and neck on quality (59.0 vs 61.9 on the BenchLeader Index, inside the ±4.5 margin), and they cost about the same at $2.15 vs $2.00 per 1M tokens blended. Muse Spark 1.3 leads in every category we measure both in. Muse Spark 1.3 streams ~2× faster.

Key facts (as of 2 Nov 2026)

GLM 5.3 scores 59.0 on the BenchLeader Index and Muse Spark 1.3 scores 61.9 (BenchLeader, 2 Nov 2026).
GLM 5.3 costs $2.15 per 1M tokens blended (list price, 2 Nov 2026).
Muse Spark 1.3 costs $2.00 per 1M tokens blended (list price, 2 Nov 2026).
Muse Spark 1.3 streams ~2× faster than GLM 5.3 (Artificial Analysis, 7-day median, 2 Nov 2026).
Of the 59 benchmarks both models have, Muse Spark 1.3 leads 44 (BenchLeader, 2 Nov 2026).
On Arena WebDev, GLM 5.3 is rated 1623 and Muse Spark 1.3 1656 (LMArena, as published by 2 Nov 2026).

GLM 5.3 benchmarks max Zhipu AI

Muse Spark 1.3 benchmarks max Meta Add a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	Either	60 vs 61 category score; Arena WebDev 1623 vs 1656	Either
Agents & tool use	Muse Spark 1.3	66 vs 58 category score; τ³-Banking (AA) 50.5% vs 50.3%	High
Maths	Muse Spark 1.3	63 vs 60 category score; FrontierMath Tiers 1–3 74.0% vs 68.8%	Medium
Reasoning	Muse Spark 1.3	61 vs 55 category score; HLE-Diamond (AA) 33.7% vs 17.9%	Medium
Knowledge	Muse Spark 1.3	59 vs 54 category score; AA-Omniscience v1.1 22.4 vs 6.0	Medium
Long documents	Muse Spark 1.3	66 vs 65 category score; AA-LCR v1.1 83.0% vs 79.7%	Medium
Chat quality (human preference)	Muse Spark 1.3	69 vs 67 on Arena votes	Medium
Lowest cost	Either	$2.15 vs $2.00 per 1M blended; agentic coding session $0.102 vs $0.092	–
Fastest first answer	GLM 5.3	23.9 s (GLM 5.3 (max)) vs 46.3 s (Muse Spark 1.3 (max)) to the first answer token	–
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

GLM 5.3 (max) and Muse Spark 1.3 (max) are neck and neck on quality (59.0 vs 61.9, within the ±4.5 margin).
Muse Spark 1.3 (max) is stronger in agents & tools, coding, human preference, knowledge, long context, maths, reasoning, multimodal.
They cost about the same ($2.00 per 1M blended).
Muse Spark 1.3 (max) streams 2.2× faster (194 vs 89 tokens per second).

At a glance

Spec	GLM 5.3	Muse Spark 1.3
Developer	Zhipu AI	Meta
Released	18 Aug 2026	2 Sep 2026
Context window (tokens)	1,000,000	1,048,576
Compared at	GLM 5.3 (max)	Muse Spark 1.3 (max)
Open weights	Yes	No
Price in / out / cached input per 1M	$1.40 / $4.40 / $0.260	$1.25 / $4.25 / $0.150

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	GLM 5.3 (max)	Muse Spark 1.3 (max)	Leader
Reasoning	55.4	60.6	Muse Spark 1.3
Coding	59.9	60.8	level
Agents & tools	57.9	65.5	Muse Spark 1.3
Maths	60.2	63.1	Muse Spark 1.3
Knowledge	53.8	58.5	Muse Spark 1.3
Human preference	67.1	68.8	Muse Spark 1.3
Multimodal	–	65.7	not comparable
Long context	64.7	66.4	Muse Spark 1.3

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

Not drawn, measured for fewer than two of these models: Instruction following, Multimodal.

ModelIndex

Where sources disagree

Across the 59 benchmarks both have, GLM 5.3 leads 14, Muse Spark 1.3 leads 44 and 1 is a tie. Every overall index that rates both puts Muse Spark 1.3 ahead.

Overall index	GLM 5.3 (max)	Muse Spark 1.3 (max)	Leader
BenchLeader Index	59.0	61.9	neck and neck
AA Intelligence Index v5.0	31.6	36.4	Muse Spark 1.3
Arena Text	1481	1495	Muse Spark 1.3

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

Measure	GLM 5.3 (max)	Muse Spark 1.3 (max)
Blended price per 1M tokens	$2.15	$2.00
Input / output per 1M	$1.40 / $4.40	$1.25 / $4.25
Cached input per 1M	$0.260	$0.150
Price per task: chat reply	$0.0019	$0.0018
Price per task: summarize a 30-page report	$0.019	$0.018
Price per task: code edit	$0.015	$0.014
Price per task: agentic coding session	$0.102	$0.092
Price per task: structured extraction	$0.0037	$0.0034
Agentic coding session, input mostly cached	$0.050	$0.043
Cost per benchmark task (AA Index)	$5.01	$2.39
Output tokens per task (AA Index)	119k	91k
Of which reasoning	85k	55k
Time per task (AA Index)	18 min	8 min
Output speed	89 tok/s	194 tok/s
Time to first answer	23.9 s	46.3 s
Time to a complete answer	29.5 s	48.9 s

Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $5.01 on GLM 5.3 (max) and $2.39 on Muse Spark 1.3 (max), and GLM 5.3 (max) wrote 1.3× as many output tokens for the same work, which a per-token price hides.

Each model is compared at its best-ranked reasoning-effort setting. GLM 5.3 (max) scores 59.0 and takes 24 s to its first answer token; GLM 5.3 (low) scores 47.5 in 27 s. Muse Spark 1.3 (max) scores 61.9 and takes 46 s to its first answer token; Muse Spark 1.3 (xhigh) scores 58.5 in 22 s, Muse Spark 1.3 scores 57.8 in 2 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

134 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	GLM 5.3 (max)	Muse Spark 1.3 (max)
BenchLeader Index	BenchLeader	59.0	61.9
Agents & tools score	BenchLeader	57.9	65.5
Coding score	BenchLeader	59.9	60.8
Human preference score	BenchLeader	67.1	68.8
Knowledge score	BenchLeader	53.8	58.5
Long context score	BenchLeader	64.7	66.4
Maths score	BenchLeader	60.2	63.1
Reasoning score	BenchLeader	55.4	60.6
Multimodal score	BenchLeader	–	65.7
Blended price $/M	BenchLeader	$2.15	$2.00
Output speed	BenchLeader	89 tok/s	194 tok/s
Time to first answer	BenchLeader	23.9 s	46.3 s
Context window	BenchLeader	1,000,000 tokens	1,048,576 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	90.9%	–
Arena Hard Prompts	Arena (LMArena)	1505	1516
LiveBench 2.0 Reasoning	LiveBench	–	89.7%†
LiveBench 1.0 Reasoning	LiveBench	85.8%†	89.7%†
GPQA Diamond (AA)	Artificial Analysis	91.7%	93.5%
Humanity's Last Exam (AA)	Artificial Analysis	42.3%	48.7%
HLE-Diamond (AA)	Artificial Analysis	17.9%	33.7%
GPQA Diamond (Vals)	Vals AI	88.1%	–
CritPt	Artificial Analysis	19.1%	24.9%
CritPt v2 hard subset (AA)	Artificial Analysis	33.5%	46.0%
MysteryMechanism	Vals AI	23.0%	36.0%
Chess Puzzles	Epoch AI Benchmarking Hub	37.0%	37.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	33.0%	25.0%
LMCA	Epoch AI Benchmarking Hub	55.5%†	53.9%†
DTBench	Epoch AI Benchmarking Hub	87.7%†	96.5%†
BTF-3	Epoch AI Benchmarking Hub	14.9%†	14.1%†
Coding
SciCode	SciCode	59.0%	58.8%
WeirdML	WeirdML	75.4%	–
FrontierCode	Cognition	40.1%	–
Arena Coding	Arena (LMArena)	1520	1534
Arena WebDev	Arena (LMArena)	1623	1656
LiveBench 2.0 Coding	LiveBench	–	90.2%†
LiveBench 1.0 Coding	LiveBench	79.0%†	81.1%†
LiveCodeBench	Vals AI	80.5%	–
IOI	Vals AI	68.4%	56.6%

Show all 134 benchmarks

Metric	Publisher	GLM 5.3 (max)	Muse Spark 1.3 (max)
Coding
SWE-bench (Vals)	Vals AI	95.4%	–
Code Migration	Vals AI	44.2%	47.4%
Code Migration v1.1	Vals AI	55.1%	–
ProgramBench	Vals AI	1.5%	2.5%
SWE-bench Multimodal	Vals AI	–	43.1%
Vibe Code Bench 1-100	Vals AI	20.0%	20.5%
Vibe Code Bench v1.1	Vals AI	78.1%	85.9%
DeepSWE v1.1	Epoch AI Benchmarking Hub	69.0%	–
CursorBench	Cursor	42.6%	41.6%
ALE-Bench	Epoch AI Benchmarking Hub	1317.4†	1688.3†
FrontierSWE	Epoch AI Benchmarking Hub	30.2%	25.8%
Terminal-Bench 4.0 (AA)	Artificial Analysis	41.9%	33.3%
Terminal-Bench 2.1 (AA)	Artificial Analysis	83.9%	84.3%
Startrise Frontend	Startrise	73.2%†	74.7%†
GameBench 2 Overall	DuelLab GameBench 2	65.7†	59.7†
GameBench 2 by reasoning setting	DuelLab GameBench 2	73.5	70.9†
FrontierCode 1.1 (AA)	Artificial Analysis	40.1%	40.6%
FrontierCode 2.0 (AA)	Artificial Analysis	21.6%	23.1%
Agents & tools
Terminal-Bench	Terminal-Bench	41.8%	14.6%†
APEX-Agents	Mercor	56.6%†	47.6%
Arena Agent	Arena (LMArena)	0.9	2.6
LiveBench Long Agentic	LiveBench	–	25.5%†
LiveBench Browser	LiveBench	–	30.9%†
LiveBench Agentic Coding	LiveBench	60.9%†	64.1%†
Terminal-Bench 2.1 (Vals)	Vals AI	71.5%	79.0%
MCP Atlas	Scale AI SEAL	84.2%†	–
HiL-Bench	Scale AI SEAL	58.3%†	66.9%†
GDPval-AA v2.1, normalised score	Artificial Analysis	57.5%	–
GDPval-AA v2.1	Artificial Analysis	1657	–
τ³-Banking (AA)	Artificial Analysis	50.3%	50.5%
ITBench SRE (AA)	Artificial Analysis	46.1%	33.2%
Analyst Agent (AA)	Artificial Analysis	38.8%	37.5%
CUA-bench	Vals AI	–	5.8%
CyberBench	Vals AI	72.1%	72.7%
Finance Agent v2	Vals AI	55.8%	60.0%
Finance Agent v2.1	Vals AI	65.0%	–
Harvey's Legal Agent Benchmark v1.1	Vals AI	14.6%	–
Harvey's Legal Agent Benchmark v1	Vals AI	8.3%	23.8%
Legal Research Bench	Vals AI	49.0%	55.3%
SkillsBench	Vals AI	47.5%	–
SREBench	Vals AI	9.2%	3.8%
Tax Agent Bench	Vals AI	39.7%	42.4%
Terminal-Bench 4.0 (Vals)	Vals AI	38.9%	24.8%
Terminal-Bench Science	Vals AI	5.7%	10.0%
Vending-Bench 2	Andon Labs	8163.6†	–
AutomationBench	Artificial Analysis	62.2%	57.9%
GDP.pdf (AA)	Artificial Analysis	11.2%	26.6%
Harvey LAB-AA v1.1	Harvey	0.3%	8.9%
EnterpriseOps-Gym	Artificial Analysis	36.4%	–
AA-Briefcase v1.1	Artificial Analysis	1505	1581
GDPx	GDPx by SemiAnalysis	2.7%	–
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	9.5%	10.9%
CWE-Bench (AA)	Artificial Analysis	55.8%	–
DeepSec-Bench (AA)	Artificial Analysis	24.3%	–
CyberGym end-to-end (AA)	Artificial Analysis	29.0%	–
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	68.8%	74.0%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	29.3%	46.3%
OTIS Mock AIME	Epoch AI Benchmarking Hub	91.1%	99.2%†
ProofBench	Vals AI	49.0%	58.0%
LiveBench Mathematics	LiveBench	87.9%†	96.0%†
Arena Maths	Arena (LMArena)	1499	1508
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	41.0%	–
LiveBench 2.0 Data Analysis	LiveBench	–	79.6%†
LiveBench Research	LiveBench	–	68.6%†
LiveBench 1.0 Data Analysis	LiveBench	70.2%†	79.6%†
AA-Omniscience v1.1	Artificial Analysis	6.0	22.4
MMLU-Pro	Vals AI	86.8%	–
LegalBench	Vals AI	84.8%	–
TaxEval	Vals AI	72.4%	–
PRBench Finance	Scale AI SEAL	–	59.5%†
PRBench Legal	Scale AI SEAL	–	61.6%†
Excel Modeling Benchmark	Vals AI	56.3%	67.4%
Excel Modeling Benchmark v1.1	Vals AI	69.1%	–
MedCode	Vals AI	42.9%	–
MedScribe	Vals AI	88.8%	–
Public Benefits Bench v1.1	Vals AI	68.5%	–
DrugDiscoveryBench	Scale AI SEAL	–	62.2%†
GDP.pdf	Epoch AI Benchmarking Hub	–	27.6%†
AA-Omniscience v1.1: accuracy	Artificial Analysis	32.3%	38.0%
AA-Omniscience v1.1: non-hallucination	Artificial Analysis	61.1%	74.8%
HealthBench Professional (AA)	OpenAI	52.8%	–
Instruction following
LiveBench Language	LiveBench	79.9%†	82.8%†
LiveBench Instruction Following	LiveBench	69.3%†	78.0%†
Arena Instruction Following	Arena (LMArena)	1479	1483
Human preference
Arena Text	Arena (LMArena)	1481	1495
Arena Creative Writing	Arena (LMArena)	1457	1464
Arena Multi-turn	Arena (LMArena)	1478	1493
Arena Longer Queries	Arena (LMArena)	1486	1496
Multimodal
Arena Vision	Arena (LMArena)	–	1308
LiveBench Design	LiveBench	–	74.8%†
MMMU-Pro	Artificial Analysis	–	82.0%†
Code2Video-AA	Artificial Analysis	1034	1019
AA-3D	Artificial Analysis	783	1033
Long context
AA-LCR v1.1	Artificial Analysis	79.7%	83.0%
Arena Document	Arena (LMArena)	–	1468
MLCR	Artificial Analysis	17.2%	13.9%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	156.2†	157.4†
LiveBench 2.0	LiveBench	–	63.0%†
LiveBench 1.0	LiveBench	76.1%†	81.6%†
AA Intelligence Index v5.0	Artificial Analysis	31.6	36.4
AA Intelligence Index v4.3.2	Artificial Analysis	44.8	48.1
AA Progress Index v1	Artificial Analysis	322.7	324.5
Vals Index	Vals AI	59.7	–
Vals Finance Index	Vals AI	60.5%	–
Vals RSI Index	Vals AI	22.9%	19.6%
Vals Router Index	Vals AI	59.7%†	–
AA Cyber Index	Artificial Analysis	36.4	–
Safety & honesty
FORTRESS	Scale AI SEAL	28.2%	–
Metadata
AA Openness Index	Artificial Analysis	33.3	–

Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261026-cb69502a12d9 (https://benchmarks.duellab.org/releases/gb2-20261026-cb69502a12d9/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

1 Nov 2026 GLM 5.3 (max): cached input price moved from $0.30/M to $0.26/M (13% down).
31 Oct 2026 GLM 5.3 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
29 Oct 2026 Muse Spark 1.3 (max): 1 score revision.
28 Oct 2026 GLM 5.3 (max): BenchLeader Index 61.3 → 58.9.
28 Oct 2026 Muse Spark 1.3 (max): BenchLeader Index 64.5 → 61.8.
28 Oct 2026 GLM 5.3 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $2.01/M to $5.01/M (150% up); cached input price moved from $0.30/M to $0.26/M (13% down).
28 Oct 2026 Muse Spark 1.3 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $1.31/M to $2.39/M (81% up).
27 Oct 2026 GLM 5.3 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
27 Oct 2026 Muse Spark 1.3 (max): cost per task moved from $3.69/M to $1.31/M (64% down).
26 Oct 2026 GLM 5.3 (max): cached input price moved from $0.30/M to $0.26/M (13% down).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs