Model cost brief
DeepSeek V4 vs Grok
A benchmark-and-cost read on DeepSeek V4-Pro, DeepSeek V4-Flash, Grok 4.3, and Grok Build 0.1 for coding agents, long-context work, tool use, and everyday production routing.
The short answer
DeepSeek wins the public benchmark-and-cost comparison right now. DeepSeek has published a technical report with detailed V4 benchmark tables, an official API price sheet, open weights, and a clear 1M-token context story. xAI has current docs for Grok 4.3 and the new Grok Build 0.1 coding model, but it has not published a comparable benchmark table for either model in the official sources reviewed here.
That makes the honest result a split verdict. DeepSeek V4-Pro-Max is the raw published benchmark leader in this head-to-head. DeepSeek V4-Flash and V4-Pro are also the total-token-cost leaders under normal API math. Grok 4.3 and Grok Build 0.1 remain worth testing if you want xAI's hosted tool ecosystem, Grok Build CLI workflow, high output speed, or a cheaper closed-model alternative to older frontier tiers. They are not the benchmark winners until xAI publishes comparable numbers or independent leaderboards settle the question.
Current product snapshot
The names are easy to mix up. DeepSeek V4 is a model family; Grok currently splits into a general flagship and a coding-specialized Build model.
| Model | Status as of May 28, 2026 | Context | Published pricing | Best current use |
|---|---|---|---|---|
| DeepSeek V4-Pro | Official API model and open-weight model. DeepSeek describes V4-Pro-Max as the maximum reasoning-effort mode of V4-Pro. | 1M tokens; maximum output listed at 384K in the API docs. | $0.435 per 1M input tokens, $0.003625 per 1M cached input tokens, $0.87 per 1M output tokens under the current official price sheet. | Cost-sensitive coding, reasoning, and long-context work where open weights or low API cost matter. |
| DeepSeek V4-Flash | Official API model and open-weight model; smaller and cheaper than Pro. | 1M tokens; maximum output listed at 384K in the API docs. | $0.14 per 1M input tokens, $0.0028 per 1M cached input tokens, $0.28 per 1M output tokens. | Cheap high-volume routing, simple agent tasks, long-context summarization, and fallback workloads. |
| Grok 4.3 | xAI's current general flagship in the docs, aliased as grok-latest. | 1M tokens. | $1.25 per 1M input tokens, $0.20 per 1M cached input tokens, $2.50 per 1M output tokens. xAI says higher context pricing applies above 200K context. | General xAI API work, multimodal text-image workflows, configurable reasoning, and hosted tool use. |
| Grok Build 0.1 | xAI's newest coding model, released to the API in public beta on May 28, 2026. | 256K tokens. | $1.00 per 1M input tokens, $0.20 per 1M cached input tokens, $2.00 per 1M output tokens. | Agentic coding in Grok Build, Cursor, OpenCode, OpenClaw, Kilo Code, and similar developer harnesses. |
What counts as a fair win
A model can win three different ways. It can win on raw benchmark score, on cost-normalized score, or on workflow fit. DeepSeek currently wins the first two in this specific comparison because it publishes benchmark evidence and charges dramatically less per token. Grok can still win a local workflow if the Grok Build product loop, xAI tools, speed, or subscription access makes your engineering process materially faster.
The missing piece is public comparability. xAI's docs make product and pricing claims for Grok 4.3 and Grok Build 0.1, but they do not give the same kind of benchmark table DeepSeek gives in the V4 technical report. That is not a small footnote. If one side has numbers and the other side has product positioning, the numbers side wins the published-benchmark round by default.
Published benchmark evidence
These rows use DeepSeek's technical report for V4. xAI rows are marked as missing where official comparable benchmark values were not found.
| Benchmark | DeepSeek V4-Pro-Max | DeepSeek V4-Flash-Max | Latest Grok public score | Read |
|---|---|---|---|---|
| LiveCodeBench v6 | 93.5 Pass@1-COT | 91.6 Pass@1-COT | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek has the published coding-generation win in this comparison. |
| Codeforces internal benchmark | 3206 rating | 3052 rating | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek's report positions V4-Pro-Max as extremely strong on contest-style coding, but this is vendor-run and not a public leaderboard row. |
| SWE Verified | 80.6% resolved | 79.0% resolved | No comparable official Grok 4.3 or Grok Build 0.1 score found. | Strong, but not frontier-leading against the newest Claude Opus 4.8 public score. |
| SWE Pro | 55.4% resolved | 52.6% resolved | No comparable official Grok 4.3 or Grok Build 0.1 score found. | Useful, but below the current Claude Opus 4.8 number from Anthropic's Opus 4.8 release. |
| Terminal Bench 2.0 | 67.9% accuracy | 56.9% accuracy | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek is credible for terminal agents, but not the current cross-vendor leader on the newer Terminal-Bench 2.1 table used in Anthropic's Opus 4.8 materials. |
| MCPAtlas Public | 73.6 Pass@1 | 69.0 Pass@1 | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek is solid on protocol-style tool use; Grok's tool-use claims need comparable evidence. |
| Toolathlon | 51.8 Pass@1 | 47.8 Pass@1 | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek again has the only official score in this head-to-head. |
| GDPval-AA | 1554 Elo | 1395 Elo | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek's professional-work signal is useful, but Claude Opus 4.8 currently has a higher published GDPval-AA score in Anthropic's table. |
| GPQA Diamond | 90.1 Pass@1 | 88.1 Pass@1 | No comparable official Grok 4.3 or Grok Build 0.1 score found. | DeepSeek is strong, but this benchmark is tightly clustered among frontier models and should not decide routing by itself. |
The cost math changes the benchmark read
Benchmark tables usually hide the bill. That is dangerous for reasoning and agentic coding because the model may spend far more tokens than the prompt suggests. DeepSeek's own V4 report makes this visible: its reasoning-effort curves compare HLE and Terminal Bench 2.0 performance against total tokens, showing that higher scores come from spending more test-time compute.
The comparison below uses simple API math, not a claim about every production run. Real costs move with cache hit rate, retries, tool calls, context length, file search, batch mode, and whether a model bills hidden reasoning tokens as output.
Example total task costs
Assumptions: standard API rates from official docs, no batch discount, no subscription cap, no retry cost. For Grok, tool fees are separate and xAI says requests above 200K context can use higher context pricing.
| Example workload | DeepSeek V4-Flash | DeepSeek V4-Pro | Grok Build 0.1 | Grok 4.3 | Practical read |
|---|---|---|---|---|---|
| 100K input + 30K output coding-agent run, no cache, no tool fees | $0.0224 | $0.0696 | $0.1600 | $0.2000 | DeepSeek V4-Pro is about 2.3x cheaper than Grok Build and 2.9x cheaper than Grok 4.3 under this token mix. V4-Flash is far cheaper still. |
| 100K cached input + 30K output repeated-agent run | $0.0087 | $0.0265 | $0.0800 | $0.0950 | DeepSeek's cache-hit pricing is the major value story for repeated repo context, retrieval packs, and long prompt prefixes. |
| 1M input + 100K output long-context run | $0.1680 | $0.5220 | Not applicable at 256K context | $1.5000 before any >200K context surcharge | DeepSeek wins long-context token economics by a wide margin. Grok 4.3 remains usable at 1M context, but the docs warn that higher context pricing can apply. |
| Same 100K + 30K Grok run with 20 xAI server-side tool calls at $5 per 1K calls | External tool cost depends on orchestrator | External tool cost depends on orchestrator | $0.2600 | $0.3000 | Hosted tools can dominate small and medium Grok runs. A cheap token price is not the same as a cheap agent. |
Who wins by workload?
Use this as a routing hypothesis, not as a substitute for a local eval on your repo, tools, and data.
| Workflow | Current winner | Why | What could change it |
|---|---|---|---|
| Raw published DeepSeek-vs-Grok benchmarks | DeepSeek V4-Pro-Max | DeepSeek publishes detailed V4 benchmark tables; xAI does not publish comparable Grok 4.3 or Grok Build 0.1 benchmark rows in the official sources reviewed here. | A comparable xAI benchmark table or strong independent leaderboard results for Grok Build 0.1. |
| Cost-normalized coding and agent tasks | DeepSeek V4-Pro or V4-Flash | DeepSeek is cheaper on input, cached input, and output tokens. It also publishes strong coding and agentic scores. | If Grok Build requires fewer retries, finishes tasks faster, or tool integration cuts human review enough to offset token cost. |
| Open-weight deployment | DeepSeek V4 | DeepSeek V4 checkpoints are available on Hugging Face under an MIT license; Grok 4.3 and Grok Build are hosted xAI services. | A future open Grok release with competitive weights and deployment economics. |
| xAI-native engineering workflow | Grok Build 0.1 | Grok Build is wired into xAI's CLI, plan/review/approve flow, MCP servers, subagents, headless mode, and developer harnesses. | DeepSeek-based agents outperforming Grok Build in the same CLI workflow with lower total task cost. |
| General hosted assistant work | Tie until tested locally | Grok 4.3 has stronger official product positioning for hosted general use; DeepSeek has stronger published cost and benchmark evidence. | Your actual tool use, latency target, data policy, region, moderation needs, and cache rate. |
| Long-context economics | DeepSeek V4-Pro or V4-Flash | DeepSeek gives 1M context on both models and much lower token costs; its report emphasizes lower FLOPs and KV cache use at 1M context. | If xAI's high-context surcharge is favorable in practice or Grok 4.3 produces materially better answers on your documents. |
How to evaluate them without fooling yourself
A fair DeepSeek-vs-Grok test should look more like a procurement experiment than a prompt-off.
- Run the same repo tasks in the same harness with fixed timeouts, tool access, and review criteria.
- Record total input, cached input, visible output, reasoning tokens if exposed, tool calls, retries, and failed-run billing.
- Separate first-pass success from final success after retries. The cheaper model can lose if it needs more attempts.
- Measure human review minutes. A slower but cleaner patch may be cheaper than a fast patch that requires cleanup.
- Test long-context retrieval separately from code editing. A 1M-token window does not automatically mean good use of 1M tokens.
- Keep xAI tool-call fees separate from token costs so the agent bill is not hidden inside the model comparison.
Bottom line
DeepSeek V4 is the stronger evidence-backed choice today if your question is benchmark performance per dollar. V4-Pro-Max has the published raw scores; V4-Pro and V4-Flash have the cost curve. That combination is hard to ignore for coding agents, long-context systems, and high-volume routing.
Grok is the more interesting product bet than the benchmark bet. Grok 4.3 is the current xAI general flagship, and Grok Build 0.1 is fresh enough that it deserves a real coding-agent eval. But until xAI publishes comparable benchmark data, Grok should be treated as a workflow candidate, not the current public benchmark winner.
DeepSeek V4 vs Grok FAQ
The common confusion is not intelligence. It is comparability.
Is DeepSeek V4 better than Grok 4.3?
On published benchmark evidence and token cost, yes. DeepSeek publishes detailed V4 benchmark tables and lower API prices. Grok 4.3 may still win in a specific xAI-native workflow, but xAI has not published comparable official benchmark scores for Grok 4.3 in the sources reviewed here.
Is Grok Build 0.1 the latest Grok model?
It is the latest xAI coding-specific model announced for the API on May 28, 2026. Grok 4.3 remains the current general flagship in xAI's model docs.
Which model is cheaper for coding agents?
DeepSeek V4 is cheaper under normal per-token math. The gap gets larger when cached prompt prefixes are reused. Grok can become more expensive when server-side tool fees, long-context surcharges, and retries are included.
Should teams migrate from Grok to DeepSeek V4?
Not from benchmark tables alone. Teams should run local tasks in the same harness, include total token and tool-call costs, and compare patch quality, review time, security posture, data rules, and failure modes.
What is the biggest unknown?
The biggest unknown is Grok Build 0.1 benchmark performance. It is new, coding-specific, and product-integrated, but official public benchmark rows were not available in the sources reviewed for this draft.
Sources
This draft uses official model docs, pricing pages, and technical reports first. Where a benchmark was not publicly available, the article says so instead of filling the gap with rumor.
Official release note confirming DeepSeek V4-Pro, V4-Flash, API availability, open weights, 1M context, and the V4 technical report.
Official DeepSeek API pricing for V4-Flash and V4-Pro, including input, cached input, output, context length, and output limits.
Technical report with V4 architecture details, benchmark tables, reasoning-effort curves, and long-context efficiency claims.
Official xAI model list showing Grok 4.3 as the current default flagship and Grok Build 0.1 as a coding model.
Official token pricing and tool invocation costs for Grok 4.3, Grok Build 0.1, web search, X search, code execution, files, and batch API.
Official Grok 4.3 page with context window, pricing, aliases, and feature claims.
xAI announcement for the public beta API release of grok-build-0.1, including speed, coding-agent positioning, and pricing.
xAI's CLI announcement explaining Grok Build's plan/review/approve flow, subagents, MCP support, and headless mode.