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elorian · Balanced

Elorian Glimpse

Added Oct 17, 2026

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Use in the app

Glimpse is Elorian's visual reasoning model for understanding images and video and answering in text. It can analyze charts, count objects, follow events over time, and reason about spatial relationships and physical cause and effect. It supports tool calling and structured output across a shared 262,144-token context window, with up to 256,000 output tokens within the remaining context.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Video input
Input
Text, Images, Video
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.63
Output
$3.15
Cache read
$0.063

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
256K
Average output (7 days)
2.8K tokens
Longer than 95% of 468 models

Side by side

Elorian Glimpse compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Elorian GlimpseelorianThis modelMiniMax M1 80KMiniMaxRemove
ProviderelorianMiniMax
Discovery tierBalancedBalanced
AddedOct 17, 2026Jan 8, 2025
Limits
Context window262.14K1MBest
Max output256KBest131.07K
Average output2.8K tokens—
Pricing, USD per 1M tokens
Input$0.63$0.61Best
Output$3.15$2.42Best
Cache read$0.063—
Benchmark indexes
Intelligence Index—11.7
Math Index—61.0
Capabilities
ReasoningYesNo
ToolsYesNo
VisionYesNo
Structured outputYesNo
Video inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Elorian Glimpse
  • MiniMax M1 80K

Intelligence Index

  • Elorian Glimpse—
  • MiniMax M1 80K11.7
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Elorian Glimpse: —
    • MiniMax M1 80K: 61.0

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Elorian Glimpse: —
    • MiniMax M1 80K: 57.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Elorian Glimpse: —
    • MiniMax M1 80K: 8.9%

  • GPQA Diamond

    Graduate-level science questions

    • Elorian Glimpse: —
    • MiniMax M1 80K: 69.7%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Elorian Glimpse: —
    • MiniMax M1 80K: 81.6%

  • IFBench

    Following precise output instructions

    • Elorian Glimpse: —
    • MiniMax M1 80K: 41.8%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Elorian Glimpse: —
    • MiniMax M1 80K: 71.1%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Elorian Glimpse: —
    • MiniMax M1 80K: 61.0%

  • AIME

    Competition mathematics

    • Elorian Glimpse: —
    • MiniMax M1 80K: 84.7%

  • MATH-500

    Competition math problems

    • Elorian Glimpse: —
    • MiniMax M1 80K: 98.0%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Elorian Glimpse: —
    • MiniMax M1 80K: 3.0%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Elorian Glimpse: —
    • MiniMax M1 80K: 34.2%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Elorian Glimpse: —
    • MiniMax M1 80K: 57.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
0.0%
About $0.63 per 1M input tokens with caching

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "elorian/glimpse",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="elorian/glimpse",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)