Decision support

Muse Spark 1.3 vs GPT-6.1 Terra

Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.

Models Hardware

Muse Spark 1.3

Benchmark results

Head to head on 5 benchmarks both models report

Muse Spark 1.30leads
GPT-6.1 Terra5leads

Arena Text
Arena rating · Higher is better
- Muse Spark 1.3
  1496
  Arena #11CI 1491 to 1501
- GPT-6.1 Terra
  Not reported
Runs and sources
Muse Spark 1.3
max149695% CI 1491 to 1501 · 26,111 votes
GPT-6.1 Terra
Not reported
Source:Arena Text leaderboard, 2026-11-09
Arena WebDev
Arena rating · Higher is better
- Muse Spark 1.3
  1655
  Arena #20CI 1648 to 1662
- GPT-6.1 Terra
  Best1679
  +23 ahead · Arena #13CI 1668 to 1689
Runs and sources
Muse Spark 1.3
xhigh162095% CI 1613 to 1627 · 11,653 votes
max165595% CI 1648 to 1662 · 12,122 votes
GPT-6.1 Terra
max167995% CI 1668 to 1689 · 3,944 votes
Source:Arena WebDev leaderboard, 2026-11-10
Arena Vision
Arena rating · Higher is better
- Muse Spark 1.3
  1291
  Arena #13CI 1283 to 1300
- GPT-6.1 Terra
  Not reported
Runs and sources
Muse Spark 1.3
xhigh128895% CI 1280 to 1296 · 7,522 votes
max129195% CI 1283 to 1300 · 7,683 votes
GPT-6.1 Terra
Not reported
Source:Arena Vision leaderboard, 2026-11-09
Arena Document
Arena rating · Higher is better
- Muse Spark 1.3
  1474
  Arena #16CI 1466 to 1482
- GPT-6.1 Terra
  Not reported
Runs and sources
Muse Spark 1.3
max147495% CI 1466 to 1482 · 7,205 votes
GPT-6.1 Terra
Not reported
Source:Arena Document leaderboard, 2026-11-09
Agent Arena
IPS score · Higher is better
- Muse Spark 1.3
  +0.022
  Arena #21CI +0.013 to +0.030
- GPT-6.1 Terra
  Best+0.120
  +0.098 ahead · Arena #8CI +0.107 to +0.133
Runs and sources
Muse Spark 1.3
max+0.02295% CI +0.013 to +0.030 · 8,894,242 observations
GPT-6.1 Terra
max+0.12095% CI +0.107 to +0.133 · 8,572,270 observations
Source:Agent Arena leaderboard, 2026-11-11
FrontierMath-Tier-4-v2-Private
Best published score · Higher is better
- Muse Spark 1.3
  46.3%
  #23 of 72
- GPT-6.1 Terra
  Best92.7%
  +46.3 pts ahead · #6 of 72
Runs and sources
Muse Spark 1.3
xhigh41.5%
max46.3%
GPT-6.1 Terra
max92.7%
Source:Epoch AI evaluation
FrontierMath-Tiers-1-3-v2-Private
Best published score · Higher is better
- Muse Spark 1.3
  74.4%
  #24 of 87
- GPT-6.1 Terra
  Best90.9%
  +16.5 pts ahead · #5 of 87
Runs and sources
Muse Spark 1.3
xhigh74.4%
max74.0%
GPT-6.1 Terra
max90.9%
Source:Epoch AI evaluation
GPQA diamond
Best published score · Higher is better
- Muse Spark 1.3
  Not reported
- GPT-6.1 Terra
  94.3%
  #10 of 161
Runs and sources
Muse Spark 1.3
Not reported
GPT-6.1 Terra
max94.3%
Source:Epoch AI evaluation
OTIS Mock AIME 2024-2025
Best published score · Higher is better
- Muse Spark 1.3
  99.2%
  #17 of 158
- GPT-6.1 Terra
  Best100.0%
  +0.8 pts ahead · #1 of 158
Runs and sources
Muse Spark 1.3
xhigh99.2%
GPT-6.1 Terra
max100.0%
Source:Epoch AI evaluation
SimpleQA Verified
Best published score · Higher is better
- Muse Spark 1.3
  Not reported
- GPT-6.1 Terra
  57.3%
  #21 of 87
Runs and sources
Muse Spark 1.3
Not reported
GPT-6.1 Terra
max57.3%
Source:Epoch AI evaluation

Each model's best published result is shown; "Not reported" means no matched evaluation, not a score of zero. Arena and DeepSWE ranks are the leaderboards' own; other ranks are among catalogue models with a score. Results from different harnesses or settings are not directly comparable.

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Arena ratings: Arena (lmarena-ai/leaderboard-dataset), licensed CC BY 4.0. Ratings come from pairwise human votes and are only comparable within one leaderboard; the interval is Arena's 95% confidence interval. Model names are matched to the Vertical Tabs catalog.

Model specifications

Release date

September 2, 2026

October 26, 2026

Context window

1.1M

Native context

—

Max output tokens

943,718

128,000

Knowledge cutoff

—

2026-06-01

Open weights

Closed

Parameter count

—

API pricing · USD per 1M tokens

Input

$1.25

$1.00

Output

$4.25

$5.00

Cached input

$0.15

$0.05

Cache write

—

$1.25

Capabilities and modalities

Input modalities

text, image, video, file

file, image, text

Output modalities

text

Tool calling

Supported

Reasoning option

Supported

Supported options

include_reasoning, max_tokens, reasoning, reasoning_effort, repetition_penalty, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_k, top_p

include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, seed, structured_outputs, tool_choice, tools, verbosity

Capabilities

—

Architecture and availability

Architecture

—

Model families

—

Tokenizer

Other

GPT

Instruction format

—

License

—

Providers

Provider endpoints

Ollama variants

Metadata source

ai-research

A dash means the field is not reported. Provider-specific performance and pricing may differ.

Benchmark results

Arena Text

Arena WebDev

Arena Vision

Arena Document

Agent Arena

FrontierMath-Tier-4-v2-Private

FrontierMath-Tiers-1-3-v2-Private

GPQA diamond

OTIS Mock AIME 2024-2025

SimpleQA Verified

Model specifications

API pricing · USD per 1M tokens

Capabilities and modalities

Architecture and availability