DeepSeek V4-Pro is DeepSeek's best model for coding — it scores 93/100 vs 87/100 for DeepSeek V3, at $0.435/1M input tokens. Across all providers, GPT-6 Astra still leads coding at 100/100 — worth considering if you're not committed to DeepSeek.
The safest deepseek model for coding default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
DeepSeek V4-Pro is the strongest answer here for deepseek model for coding — pick it when quality of output matters more than the $0.43/1M/1M input you pay for it.
DeepSeek V4-Flash handles the same job for about 68% less per token. Start here and only move up if the output is not good enough.
DeepSeek V3 is the fastest of these for deepseek model for coding — worth it when latency is what the reader notices, not the last few points of reasoning depth.
DeepSeek V4-Pro leads DeepSeek's lineup for coding at 93/100 ($0.435/1M input, 1M context).
DeepSeek V4-Flash is the value pick at $0.14/1M input with a coding score of 87/100.
GPT-6 Astra (OpenAI) is the overall coding leader at 100/100 if provider choice is open.
Choose DeepSeek V4-Pro when coding quality is the priority and you're staying on DeepSeek.
Choose DeepSeek V4-Flash when token volume matters more than peak quality.
Teams open to other providers should also evaluate GPT-6 Astra before committing.
Switch the scoring lens to see whether the deepseek model for coding answer changes when cost, speed, or long-document depth leads the decision.
DeepSeek / Budget / Aug 6, 2026
Best open-weights flagship — near-frontier coding at a tenth of the price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need vision input, verified agentic performance, or predictable pricing (surge pricing and an announced increase loom).
Where the deepseek model for coding recommendation shifts once you weigh price or latency differently.
Best open-weights flagship — near-frontier coding at a tenth of the price.
GPT-4o-class coding quality at under $0.30/1M — the best value in the directory.
Best agentic capability per dollar in the directory.
Open-source o1-class reasoning at a fraction of the cost.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| DeepSeek V4-ProDeepSeek | $0.43/1M | $0.87/1M | $6.09 | 1M tokens | Balanced | 93 | 80 | 85 |
| DeepSeek V3DeepSeek | $0.27/1M | $1.10/1M | $4.90 | 128k tokens | Fast | 87 | 74 | 80 |
| DeepSeek V4-FlashDeepSeek | $0.14/1M | $0.28/1M | $1.96 | 1M tokens | Fast | 87 | 74 | 78 |
| DeepSeek R1DeepSeek | $0.55/1M | $2.19/1M | $9.88 | 128k tokens | Deliberate | 84 | 60 | 89 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for deepseek model for coding, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for deepseek model for coding: 93/100 on coding, with the widest margin of anything in this line-up.
DeepSeek's 1.6T-parameter (49B active) MoE flagship with hybrid sparse attention — near-frontier coding and reasoning at roughly a tenth of closed-rival pricing, MIT-licensed open weights.
You need vision input, verified agentic performance, or predictable pricing (surge pricing and an announced increase loom).
The open-weights frontier flagship of 2026. Self-reported numbers flatter it and independent agentic scores land lower, but even discounted it's the most capability per dollar in the directory's upper tier — with MIT-licensed weights.
Full pricing, benchmark table and release notes on the DeepSeek V4-Pro page.
The fastest model in this shortlist for deepseek model for coding. Pick it when turnaround is what your readers or users notice.
Open-source frontier model from DeepSeek that matches GPT-4o class performance at a fraction of the cost — the most disruptive budget option for coding and general tasks.
Your team has data sovereignty requirements or needs enterprise-grade reliability guarantees.
The most cost-efficient model for GPT-4o-class coding quality. Hard to beat on value per token for engineering teams.
Full pricing, benchmark table and release notes on the DeepSeek V3 page.
The value option for deepseek model for coding: about 68% less per token than DeepSeek V4-Pro, at 87/100 on coding. Worth starting here and moving up only if the output disappoints.
Best agentic capability per dollar in the directory. Full DeepSeek V4-Flash review →
Rounds out the shortlist for deepseek model for coding at 84/100 on coding.
Open-source o1-class reasoning at a fraction of the cost. Full DeepSeek R1 review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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DeepSeek V4-Pro — it scores 93/100 on coding in this directory, ahead of DeepSeek V3 at 87/100. Best open-weights flagship — near-frontier coding at a tenth of the price.
Not overall. GPT-6 Astra (OpenAI) leads the directory for coding at 100/100 vs DeepSeek V4-Pro's 93/100. DeepSeek V4-Pro is the best pick if you're staying within DeepSeek's ecosystem.
DeepSeek V4-Flash at $0.14/1M input tokens (coding score: 87/100). Use it for volume work and reserve DeepSeek V4-Pro for the tasks where quality matters most.
$0.435/1M input tokens and $0.87/1M output tokens via the API. Context window: 1M tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $6.09, against $1.96 for DeepSeek V4-Flash.
Independent harnesses report much lower agentic scores than the self-reported numbers; trails GPT-5.6 and Opus-class on hard agentic evals. Peak-hour surge pricing doubles rates, a price increase is announced, and it's text-only (no vision). Concretely, avoid it if you need vision input, verified agentic performance, or predictable pricing (surge pricing and an announced increase loom). If none of that is negotiable, GPT-6 Astra (OpenAI) is the cross-provider leader at 100/100.
repository-level coding — 80.6% SWE-bench Verified (self-reported), the top open-weights score at release, competitive-programming-grade reasoning (Codeforces rating 3206), and self-hosted frontier capability under an MIT license. Its 1M-token context window is the practical limit on how much you can hand it in one go.
DeepSeek V4-Pro scores 93/100 on coding against 87/100 for DeepSeek V4-Flash, at 3x the input price. That premium is worth it on work where a wrong answer costs real time or money, and hard to justify on high-volume, low-stakes calls. Most teams run both and route by task rather than picking one.