"My favorite model is DeepSeek-V4-Flash-0424. Before 0731 came out, I handed almost every non-coding task to 0424. Its i… This is a necessary excerpt; read the original source for full context.
Interpretation:
The long-term user has high regard for the 0424 version (the April 24 version): its intelligence is sufficient for non-coding tasks (writing, organizing information, everyday Q&A, and so on)
With a monthly cost of only a few dozen yuan, it occupied the role of a "low-cost everyday workhorse"
The user expresses strong dissatisfaction with the 0731 version's price increase (RMB 2 for input and RMB 4 for output per million tokens during peak hours, double the April preview version)
"After deepseek raised its prices, should I switch to luna on an opencode go subscription? Even though the official site… This is a necessary excerpt; read the original source for full context.
Interpretation:
Against the backdrop of the price increase, the user compares GPT-5.6 Luna and DeepSeek-V4-Flash within an OpenCode Go subscription (billed against a $12 allowance)
Practical result: even though the official messaging says Luna is more cost-effective, the actual cost of completing tasks is still lower with deepseek-v4-flash
Key factor: DeepSeek's cache-hit rate is very high (official cached-input pricing is as low as RMB 0.02 per million tokens), substantially reducing the effective cost
The price increase was the hottest V4-Flash topic in the X community in mid-August
The two posts offer a contrast: a long-time user misses the 0424 version's value for money (wuyiqun), while a newer user finds that, after the 0731 price increase, its high cache-hit rate still makes it better than Luna in a subscription scenario (ch1lam)
This indirectly confirms the decisive effect of "cache hits" on actual bills under DeepSeek's official peak/off-peak pricing mechanism
DeepSeek V4 Flash
