DeepSeek-V4.1-Flash-1017 vs GPT-4.5
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 19.9. DeepSeek-V4.1-Flash-1017 is 178.6x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 19.9, ranking #15 overall.
On price, DeepSeek-V4.1-Flash-1017 is roughly 178.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 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 DeepSeek-V4.1-Flash-1017
- overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 178.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
Choose GPT-4.5
- you want predictable pricing at $75.00/M input and $150.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 26 for GPT-4.5
DeepSeek-V4.1-Flash-1017 and GPT-4.5don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 250.0x cheaper than GPT-4.5 ($75.00/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 125.0x cheaper than GPT-4.5 ($150.00/1M tokens).
In conclusion, GPT-4.5 is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to GPT-4.5's 128,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while GPT-4.5 is limited to 4,096 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and GPT-4.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
GPT-4.5
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 is licensed under MIT, while GPT-4.5 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GPT-4.5 was released on 2025-02-27.
DeepSeek-V4.1-Flash-1017 is 20 months newer than GPT-4.5.
Oct 17, 2026
2 days ago
1.6yr newerFeb 27, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4.1-Flash-1017 is available from DeepSeek. GPT-4.5 is available from OpenAI.
DeepSeek-V4.1-Flash-1017
GPT-4.5
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and GPT-4.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs GPT-4.5.
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