GPT-6 Astra vs Phi-3.5-mini-instruct
GPT-6 Astra leads the LLM Stats Score 60.7 to -3.8. Phi-3.5-mini-instruct is 200.0x cheaper per token.
OpenAI · Microsoft · Updated for 2026
Which is better?
GPT-6 Astra leads the overall LLM Stats Score 60.7 to -3.8, ranking #1 overall.
In the 1 individual benchmarks reported for both models, GPT-6 Astra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Phi-3.5-mini-instruct is roughly 200.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Astra also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Astra
- overall performance matters — it scores 60.7 and ranks #1 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Phi-3.5-mini-instruct
- cost matters — it's about 200.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for GPT-6 Astra · 31 for Phi-3.5-mini-instruct
GPT-6 Astra outperforms in 1 benchmarks (GPQA), while Phi-3.5-mini-instruct is better at 0 benchmarks.
GPT-6 Astra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Astra ($10.00/1M tokens) is 100.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 500.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
In conclusion, GPT-6 Astra is more expensive than Phi-3.5-mini-instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Astra accepts 1,050,000 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Astra supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.
GPT-6 Astra can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Astra
Phi-3.5-mini-instruct
License
Usage and distribution terms
GPT-6 Astra is licensed under a proprietary license, while Phi-3.5-mini-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-6 Astra was released on 2026-09-03, while Phi-3.5-mini-instruct was released on 2024-08-23.
GPT-6 Astra is 25 months newer than Phi-3.5-mini-instruct.
Sep 3, 2026
0 days ago
2.0yr newerAug 23, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a documented knowledge cutoff of 2026-04-30, while Phi-3.5-mini-instruct's cutoff date is not specified.
We can confirm GPT-6 Astra's training data extends to 2026-04-30, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.
Apr 2026
—
Provider Availability
GPT-6 Astra is available from OpenAI. Phi-3.5-mini-instruct is available from Azure.
GPT-6 Astra
Phi-3.5-mini-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs Phi-3.5-mini-instruct.