DeepSeek V3.2 vs Grok 4
In our testing DeepSeek V3.2 is the better all-around pick for most users: it wins more head-to-head benchmarks (3 vs 2) and costs a tiny fraction of Grok 4. Grok 4, however, outperforms DeepSeek on classification (4 vs 3) and tool calling (4 vs 3) and adds multimodal/file inputs—worth it if those specific capabilities matter and budget is secondary.
deepseek
DeepSeek V3.2
Benchmark Scores
External Benchmarks
Pricing
Input
$0.260/MTok
Output
$0.380/MTok
modelpicker.net
xai
Grok 4
Benchmark Scores
External Benchmarks
Pricing
Input
$3.00/MTok
Output
$15.00/MTok
modelpicker.net
Benchmark Analysis
We ran the two models across our 12-test suite and report exact scores and ranks from our testing. Wins: DeepSeek V3.2 beats Grok 4 on structured_output (5 vs 4) — DeepSeek is tied for 1st with 24 others (top tier) while Grok ranks 26 of 54 — meaning DeepSeek is clearly stronger at JSON/schema compliance and strict format adherence. DeepSeek also wins creative_problem_solving (4 vs 3; ranks 9 of 54 for DeepSeek vs 30 of 54 for Grok), and agentic_planning (5 vs 3) — DeepSeek is tied for 1st on agentic planning while Grok sits much lower (rank 42 of 54), so DeepSeek will decompose goals and recover from failures better in our tests. Grok 4 wins tool_calling (4 vs 3) — Grok ranks 18 of 54 vs DeepSeek 47 of 54, indicating Grok is better at function selection, argument accuracy and sequencing in our tool-calling tests. Grok also wins classification (4 vs 3) — Grok is tied for 1st with 29 others while DeepSeek ranks 31 of 53, so Grok is the safer choice for routing and tagging tasks. Ties (identical scores in our tests): strategic_analysis (5/5), constrained_rewriting (4/4), faithfulness (5/5), long_context (5/5) — both models tie for 1st on long_context — safety_calibration (2/2), persona_consistency (5/5), and multilingual (5/5). In practice this means both models are equally strong on reasoning tradeoffs, handling 30K+ contexts, multilingual output, and resisting persona injection in our benchmarks. Overall: DeepSeek dominates structured outputs and agentic workflows while Grok leads on classification and tool integration, with both matching on long-context and faithfulness.
Pricing Analysis
DeepSeek V3.2: $0.26 input / $0.38 output per mTok. Grok 4: $3 input / $15 output per mTok. Assuming a 50/50 input/output token split: for 1M tokens/month DeepSeek costs $320 (500 mTok input × $0.26 = $130; 500 mTok output × $0.38 = $190) vs Grok $9,000 (500×$3 = $1,500; 500×$15 = $7,500). At 10M tokens/month multiply those totals by 10 (DeepSeek $3,200 vs Grok $90,000); at 100M multiply by 100 (DeepSeek $32,000 vs Grok $900,000). The cost gap matters for high-volume production: startups, consumer chat apps, and cost-conscious APIs will favor DeepSeek; organizations needing Grok’s multimodal input, parallel tool calling, or classification accuracy must budget accordingly.
Real-World Cost Comparison
Bottom Line
Choose DeepSeek V3.2 if: you need top-tier structured output (5/5, tied for 1st), strong agentic planning (5/5, tied for 1st), creative problem solving (4/5), and a dramatically lower cost (example: $320 vs $9,000 per 1M tokens under a 50/50 split). Choose Grok 4 if: your workload depends on classification accuracy (4/5, tied for 1st), robust tool calling (4/5, rank 18 of 54), or multimodal inputs (text+image+file) and you can absorb much higher token costs.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.