Model crosswalk
Side-by-side on price, capability and workload. Both columns use the cheapest provider for that model.
DeepSeek V3.2
vs
Mistral Large 2
DeepSeek V3.2A
DeepSeek V3.2
671B params · 131K context · deepseek
Cheapest providertogether-ai
$/1M input$270000.00
$/1M output$1100000.00
Mistral Large 2B
Mistral Large 2
123B params · 131K context · mistral-research
Cheapest provideropenrouter
$/1M input$1800000.00
$/1M output$5400000.00
Specs and cheapest providers
| Spec | DeepSeek V3.2 | Mistral Large 2 |
|---|---|---|
| Parameters | 671B | 123B |
| Context window | 131K tokens | 131K tokens |
| License | deepseek | mistral-research |
| Released | 2025-05-07 | 2024-07-24 |
| Cheapest provider | ||
| Provider | together-ai | openrouter |
| Input / 1M tokens | $270000.00🏆 | $1800000.00 |
| Output / 1M tokens | $1100000.00🏆 | $5400000.00 |
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Benchmark comparison
No benchmark data available for either model yet.
Sample workload — 5M in + 2M out per month
using each model's cheapest providerWhat changes at scale
Output tokens dominate cost above a 1:3 input/output ratio. Below 1:1, input dominates and cheaper-input providers win regardless of headline price.
1M in · 250K out$545000.00 · $3150000.00
5M in · 2M out$3550000.00 · $19800000.00
20M in · 10M out$16400000.00 · $90000000.00
100M in · 60M out$93000000.00 · $504000000.00
Capability vs price
scatter// scatter: benchmark × $/1M out
Calculate cost for your workload
Compare total monthly cost across providers for DeepSeek V3.2 and Mistral Large 2 using your own input/output token mix.
Open workload calculator →Editor's take
[Mistral Large 2](/models/mistralai--mistral-large-2) is a dense model in the 123B parameter range, Mistral AI's flagship for enterprise reasoning tasks. [DeepSeek V3.2](/models/deepseek--deepseek-v3.2) operates at 671B total sparse MoE with ~37B active parameters — a fundamentally different compute profile. At comparable hosted providers, Mistral Large 2 runs $2–3/M input tokens; DeepSeek V3.2 frequently undercuts $0.50/M on providers with MoE-optimized kernels.
On benchmark comparisons, DeepSeek V3.2 leads on MATH and competitive coding tasks, consistent with its RLHF tuning targeting reasoning depth. Mistral Large 2 holds competitive positions on multilingual benchmarks and function-calling accuracy, where Mistral's training emphasis on European language coverage and structured outputs shows tangibly.
Mistral Large 2 is the choice for workloads where European data residency matters — Mistral AI offers EU-hosted inference with contractual data processing terms that most DeepSeek providers cannot match today. For GDPR-constrained pipelines, legal document analysis with EU data, or enterprise contracts requiring European provider SLAs, Mistral Large 2's provider ecosystem is more mature.
DeepSeek V3.2 is the cost-performance default for reasoning, code generation, and long-context summarization without geographic data constraints. The 4–6× pricing advantage over Mistral Large 2 at equivalent provider tiers makes it difficult to justify Mistral for purely technical workloads.
Pick Mistral Large 2 if European data residency, multilingual performance, or Mistral's enterprise support tier are requirements. Pick DeepSeek V3.2 for general-purpose reasoning and code tasks where per-token cost is the primary optimization target and data residency is not a constraint.
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