DeepSeek V4 Flash (Preview → 2026-07-31)

• Terminal Bench: 56.9 → 82.7 (+25.8)

• Toolathlon: 51.8 → 70.3 (+18.5)

Compared to GPT-5.6 Terra:

• Terminal Bench: Flash 82.7 vs Terra 78.4

• Toolathlon: Flash 70.3 vs Terra 53.1

• DeepSWE: Flash 54.4 vs Terra 69.6

• Agents' Last Exam: Flash 25.2 vs Terra 50.4

Trading blows with Terra, which is pretty interesting. No clear winner on these benchmarks, and wildy differeing scores. Very interesting!

This is more exciting than k3, IMO. Dsv4 models are extremely cheap to serve. Improving their capabilities has lots of downstream effects, as it becomes "good enough" for more and more tasks.

DS was serving the pro version at extremely low prices for a long time, and they've had integrations with opencode & other providers, so they likely gathered a lot of data from real developers doing real tasks (on openrouter they were labeled as such). Now they can use those live scenarios to further post-train their models and improve them further.

Can't wait to see if distilling k3 into dsv4 brings additional improvements. Anyway, having fast cheap models getting better is great for the community. Especially since these don't "go away" on a provider's whim. Whatever capabilities they get, can be used "forever" going forward. And, at least flash can be ran "at home" with <10k in hardware, which isn't really possible / feasible with glm/k3 larger models.

In case people want to run it, it's DeepSeek-V4-Flash-284B-A13B. So it should just barely run on a single B300, and it's small enough that it'll barely run on an M5 Max too.

They're always very understated in their update descriptions. This is actually a HUGE improvement in the model's capabilities rather than just a small tweak.

I wouldn't doubt GPT 4.6 Luna being in the top left quadrant's center on the Cost per Intelligence Index is not concerning for Liang Wenfeng. You have to remember DeepSeek v4 flash even though a bit cheaper, does not have vision abilities, which is a big draw for agentic tasks.

I admire DeepSeek's openness, but even they have been raising prices after their discounts.

Hooray! This model makes me very optimistic about the future of local inference. The CyberGym score stands out to me.

Woah, a 200B model competing with GLM-5.2 and getting close to Opus 4.8. Quite impressive.

If those numbers translate well to its general capabilities, with the great caching DeepSeek has, I feel like this model will get tons of usage.

Wonder how good the proper version of V4 Pro will be.

I'm still considering pulling the trigger on the annual subscription of Kimi for K3 but it's sometimes slower than I'd like (at least when compared to Anthropic) even on their Vivace plan, and the token limits on the GLM Coding subscription for GLM 5.2 were too easy to hit.