DeepSeek-V4-Flash-0731 vs GPT OSS 120B
Comparing DeepSeek-V4-Flash-0731 and GPT OSS 120B across benchmarks, pricing, and capabilities.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and GPT OSS 120B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4-Flash-0731 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 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 benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- cost matters — it's about 1.6x 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 Jul 2026
Choose GPT OSS 120B
- you want predictable pricing at $0.09/M input and $0.45/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and GPT OSS 120Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) costs the same as GPT OSS 120B ($0.09/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 2.5x cheaper than GPT OSS 120B ($0.45/1M tokens).
In conclusion, GPT OSS 120B is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 187.2B more parameters than GPT OSS 120B, making it 160.3% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to GPT OSS 120B's 131,072 tokens. GPT OSS 120B can generate longer responses up to 131,072 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while GPT OSS 120B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while GPT OSS 120B was released on 2025-08-05.
DeepSeek-V4-Flash-0731 is 12 months newer than GPT OSS 120B.
Jul 31, 2026
3 weeks ago
12mo newerAug 5, 2025
1.1 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-Flash-0731 is available from DeepInfra, Novita, Fireworks. GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq.
DeepSeek-V4-Flash-0731
GPT OSS 120B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and GPT OSS 120B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs GPT OSS 120B.