DeepSeek V3.2 vs GPT-5.4 Mini
For most production use cases that balance capability and cost, DeepSeek V3.2 is the pragmatic pick because it ties on 9 of 12 benchmarks while costing far less. GPT-5.4 Mini wins the two decisive tests (tool calling and classification) and adds multimodal inputs — pick it when tool selection and routing accuracy matter more than raw price.
deepseek
DeepSeek V3.2
Benchmark Scores
External Benchmarks
Pricing
Input
$0.260/MTok
Output
$0.380/MTok
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openai
GPT-5.4 Mini
Benchmark Scores
External Benchmarks
Pricing
Input
$0.750/MTok
Output
$4.50/MTok
modelpicker.net
Benchmark Analysis
Across our 12-test suite in our testing: DeepSeek V3.2 and GPT-5.4 Mini tie on nine tasks, GPT-5.4 Mini wins two, and DeepSeek wins one. Detailed breakdown (score A = DeepSeek, B = GPT-5.4 Mini; ranks are from our comparative tests):
- Structured output: A 5 vs B 5 — tie; both tied for 1st (tied with 24 others). This means both reliably follow JSON/schema formats in our tests.
- Classification: A 3 vs B 4 — GPT-5.4 Mini wins; GPT is tied for 1st on classification (tied with 29 others) while DeepSeek ranks 31 of 53. Expect more accurate routing/categorization from GPT in our tests.
- Long context: A 5 vs B 5 — tie; both tied for 1st (36-model tie). Both handle 30K+ token retrieval tasks well in our testing.
- Constrained rewriting: A 4 vs B 4 — tie; both rank 6 of their peer pools. Both are competent at tight character-limit compression in our suite.
- Creative problem solving: A 4 vs B 4 — tie; both rank 9 of 54. Expect similar ideation quality on non-obvious tasks.
- Tool calling: A 3 vs B 4 — GPT-5.4 Mini wins; GPT ranks 18 of 54 vs DeepSeek 47 of 54 in our tests. In workflows requiring accurate function selection and argument sequencing, GPT performed better for us.
- Faithfulness: A 5 vs B 5 — tie; both tied for 1st (32-model tie). Both are conservative about sticking to source material in our tests.
- Classification of agentic planning: A 5 vs B 4 — DeepSeek V3.2 wins agentic planning; DeepSeek ties for 1st on agentic planning whereas GPT ranks 16. DeepSeek is stronger in goal decomposition and failure recovery in our testing.
- Persona consistency: A 5 vs B 5 — tie; both tied for 1st.
- Multilingual: A 5 vs B 5 — tie; both tied for 1st.
- Strategic analysis: A 5 vs B 5 — tie; both tied for 1st.
- Safety calibration: A 2 vs B 2 — tie; both rank 12 of 55. Both models showed similar refusal/allow behavior in our tests. Summary: GPT-5.4 Mini outperforms DeepSeek specifically on classification (4 vs 3) and tool calling (4 vs 3) with substantially better ranks on tool calling (rank 18 vs rank 47). DeepSeek’s clear edge is agentic planning (5 vs 4). The nine ties indicate comparable real-world behavior on structure, reasoning, context length, multilingual output, and faithfulness in our testing.
Pricing Analysis
Pricing (input+output per m-token): DeepSeek V3.2 = $0.26 + $0.38 = $0.64; GPT-5.4 Mini = $0.75 + $4.50 = $5.25. At scale (assuming 1 m-token = 1,000 tokens): 1M tokens/month ≈ DeepSeek $640 vs GPT-5.4 Mini $5,250; 10M tokens ≈ $6,400 vs $52,500; 100M tokens ≈ $64,000 vs $525,000. The ~8.4% price ratio (DeepSeek vs GPT) means cost-sensitive, high-throughput apps (chat APIs, large-batch processing) should favor DeepSeek; teams prioritizing best-in-class tool calling or classification should budget for GPT-5.4 Mini despite the ~8x higher per-m-token cost.
Real-World Cost Comparison
Bottom Line
Choose DeepSeek V3.2 if you need a high-volume, cost-sensitive production model that ties on most benchmarks and scores 5/5 on agentic planning, long context, faithfulness, persona consistency, and multilingual tasks. Choose GPT-5.4 Mini if your product depends on robust tool calling and classification (scores 4 vs 3) or requires multimodal inputs (text+image+file→text) and you can absorb the higher per-m-token cost ($5.25 vs $0.64).
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.