Model profile
openai

OpenAI: GPT-4.1 Mini

OpenAI: GPT-4.1 Mini is a budget multimodal generalist from openai with a fast runtime profile, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalFast latencyLarge contextBudget pricing
Intelligence
22.9

Benchmark blend

Coding
18.5

Dev workflow signal

Context
1048K Tokens

Large

Input Price
$0.40

Budget tier

Decision snapshot
54

OpenAI: GPT-4.1 Mini currently reads as a budget multimodal option with large context and a fast runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
Fast
Price tier
Budget
Source coverage
OpenRouterArtificial AnalysisVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
22.9
23

General reasoning and benchmark headroom.

Limited
Speed
72 tok/s
74

TTFT 0.47s

Competitive
Context
1048K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$0.40
86

$1.60 output / 1M

Efficient

Editorial Profile

OpenAI: GPT-4.1 Mini in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 19Math score 46Vision enabled

GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard instruction evals, 35.8% on MultiChallenge, and 84.1% on IFEval. Mini also shows strong coding ability (e.g., 31.6% on Aider’s polyglot diff benchmark) and vision understanding, making it suitable for interactive applications with tight performance constraints.

Identity

openai multimodal profile

Positioning

Long-context research / Multimodal with large context and fast runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

  • Latency and throughput look responsive enough for interactive loops.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
22.9
MMLU Pro
78.1%
GPQA
66.4%
HLE
4.6%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
18.5
LiveCodeBench
0.483
SciCode
40.4%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
46.3
AIME
43.0%
AIME 2025
46.3%
Math 500
92.5%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
38.3%
TAU2
52.9%
TerminalBench Hard
7.6%
LCR
42.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1048K Tokens
Vision
Enabled
Modalities
text, image, file->text, file
Tokenizer
GPT
Max Completion
32768
Moderation
Yes
Supported Parameters
max_tokensresponse_formatseedstructured_outputstemperaturetool_choicetoolstop_p
Input Modalities
imagetextfile
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.40
Output
per 1M output tokens
$1.60
Blended
AA 3:1 mix
$0.70

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

OR Web Search Price
$0.0100
OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.