Head-to-head · multimodal vs multimodal

GPT-4.1 Vision vs Mistral Large 3 Instruct: which model should you choose?

We compared GPT-4.1 Vision and Mistral Large 3 Instruct on price, context window and 12 benchmarks. GPT-4.1 Vision has the stronger average benchmark score; Mistral Large 3 Instruct is cheaper on a blended 3:1 basis.

OpenAI

GPT-4.1 Vision

GPT-4.1 Vision is a multimodal model from OpenAI. It offers a 1,000,000-token context window, costs $14.88 per million input tokens and $81.24 per million output tokens, and averages 82.0 across the index's benchmark suite.

Input
$14.88 / 1M
Output
$81.24 / 1M
Context
1,000,000
Avg score
82.0
Open weights
No
Full GPT-4.1 Vision page
Mistral AI

Mistral Large 3 Instruct

Mistral Large 3 Instruct is a multimodal model from Mistral AI. It offers a 400,000-token context window, costs $5.31 per million input tokens and $22.47 per million output tokens, and averages 81.1 across the index's benchmark suite.

Input
$5.31 / 1M
Output
$22.47 / 1M
Context
400,000
Avg score
81.1
Open weights
Yes
Full Mistral Large 3 Instruct page

Specification comparison

SpecGPT-4.1 VisionMistral Large 3 InstructEdge
Input price / 1M$14.88$5.31B
Output price / 1M$81.24$22.47B
Context window1,000,000400,000A
Max output8,19265,536B
Average score82.081.1A
Arena Elo1451.81446.2A
Open weightsNoYesB

Benchmark comparison

GPT-4.1 Vision wins 9, Mistral Large 3 Instruct wins 3, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkGPT-4.1 VisionMistral Large 3 InstructGapWinner
MMLU-Pro84.082.31.7GPT-4.1 Vision
GPQA Diamond79.379.80.5Mistral Large 3 Instruct
SWE-bench Verified72.471.90.5GPT-4.1 Vision
HumanEval86.884.22.6GPT-4.1 Vision
MATH-50087.583.44.1GPT-4.1 Vision
AIME 202577.276.21.0GPT-4.1 Vision
LiveCodeBench74.375.10.8Mistral Large 3 Instruct
IFEval88.787.61.1GPT-4.1 Vision
TruthfulQA84.485.51.1Mistral Large 3 Instruct
HellaSwag89.789.10.6GPT-4.1 Vision
MMMU77.576.51.0GPT-4.1 Vision
Arena Elo1451.81446.25.6GPT-4.1 Vision

Price analysis

On a blended 3:1 input-to-output basis, GPT-4.1 Vision costs about $31.47 per million tokens and Mistral Large 3 Instruct costs about $9.60. Mistral Large 3 Instruct is roughly 69% cheaper than GPT-4.1 Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

GPT-4.1 Vision has the larger context window at 1,000,000 tokens, compared with 400,000 for Mistral Large 3 Instruct. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, GPT-4.1 Vision wins 9, Mistral Large 3 Instruct wins 3, and 0 are tied. On the index average, GPT-4.1 Vision leads Mistral Large 3 Instruct by 0.9 points (82.0 versus 81.1).

The price picture favours Mistral Large 3 Instruct. The context picture favours GPT-4.1 Vision. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.

If you need a single default, start with GPT-4.1 Vision for quality-sensitive work and Mistral Large 3 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose GPT-4.1 Vision if

  • You want the higher average benchmark score in this index.
  • You need the larger 1,000,000-token context window.

Choose Mistral Large 3 Instruct if

  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 65,536-token output limit.
  • You need open weights for self-hosting or fine-tuning.

FAQ

Is GPT-4.1 Vision better than Mistral Large 3 Instruct?

On the index average, GPT-4.1 Vision leads Mistral Large 3 Instruct by 0.9 points (82.0 versus 81.1). The better choice depends on price, context and your task. GPT-4.1 Vision wins 9 benchmarks, Mistral Large 3 Instruct wins 3.

Which is cheaper, GPT-4.1 Vision or Mistral Large 3 Instruct?

Mistral Large 3 Instruct is cheaper on a blended 3:1 basis at about $9.60 per million tokens, versus $31.47 for GPT-4.1 Vision.

Which has the larger context window?

GPT-4.1 Vision has the larger context window at 1,000,000 tokens. Mistral Large 3 Instruct has 400,000 tokens.

Are these models open weights?

GPT-4.1 Vision is proprietary; Mistral Large 3 Instruct is open weights.

Which should I choose for production?

If you need a single default, start with GPT-4.1 Vision for quality-sensitive work and Mistral Large 3 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Related comparisons