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AnthropicvsDeepSeek

Claude Haiku 4.5 vs DeepSeek V4 Pro 0813

Side-by-side technical showdown between Claude Haiku 4.5 and DeepSeek V4 Pro 0813 on TheModelverse. Compare verified LLM benchmark scores, quantization compression, local GPU hardware sizing, and API inference pricing.

Executive Showdown & Winner Breakdown

Who Wins Where: Claude Haiku 4.5 vs DeepSeek V4 Pro 0813

Verified across benchmarks, pricing & local VRAM footprint
API Cost & Token Economics
1% cheaper
Leader:DeepSeek V4 Pro 0813($1.00 vs $1.32 / 1M in)

DeepSeek V4 Pro 0813 delivers significantly lower input/output token pricing for high-throughput production.

Local Portability & Sovereignty
Self-Hostable
Leader:DeepSeek V4 Pro 0813(Open Weights vs Closed API)

DeepSeek V4 Pro 0813 can be deployed on private GPUs, Ollama, and on-prem clusters without third-party vendor lock-in.

Hardware Sizing & Model Compression

LLM Hardware Sizing & Quantization Sizing

Simulate weight compression levels and dynamic KV-cache expansion to verify whether these models fit on your local hardware or cloud GPU cluster.

Quantization Level
Active Precision
4 bits / parameter
VRAM Reduction
-72.5% vs FP16
Benchmark Retention
96–98% (Sweet Spot)
Context Simulator
Total VRAM Footprint @ 8k Context (INT4 (GGUF / AWQ))
Model 1Cloud Hosted

Claude Haiku 4.5

Zero Local VRAM
Inference runs fully on provider cloud infrastructure. Zero GPU required locally.
Total Params:
Proprietary
Active Compute:
Dense
Attention Scheme:
GQA / Multi-Head
Max Context:
200k tokens
Target Hardware: Zero Local VRAM (Managed Cloud API)
Model 2Cloud Hosted

DeepSeek V4 Pro 0813

Zero Local VRAM
Inference runs fully on provider cloud infrastructure. Zero GPU required locally.
Total Params:
Open Weights
Active Compute:
Dense
Attention Scheme:
MLA (Multi-Head Latent)
Max Context:
1000k tokens
Target Hardware: Zero Local VRAM (Managed Cloud API)
GPU & Hardware Tier Compatibility Matrix
Hardware ConfigurationAvailable VRAMClaude Haiku 4.5DeepSeek V4 Pro 0813
16 GB VRAM
RTX 4070 / 4080 (16GB), Mac M-Series (16GB)
16 GBCloud APICloud API
24 GB VRAM
1x RTX 3090 / 4090 (24GB), Mac M-Series (32GB)
24 GBCloud APICloud API
48 GB VRAM
2x RTX 4090 (TP=2), 1x L40S, Mac M-Series (64GB)
48 GBCloud APICloud API
80 GB VRAM
1x NVIDIA A100 / H100 (80GB), Mac Studio (128GB)
80 GBCloud APICloud API
160 GB Node
2x H100 (TP=2), 4x L40S, Mac Studio (192GB)
160 GBCloud APICloud API
Multi-Node Cluster
4x–8x H100 Datacenter Cluster
320 GBCloud APICloud API
LLM Benchmark Database

LLM Benchmark Showdown & Head-to-Head Deltas

Normalized evaluation scores across code generation, advanced reasoning, mathematics, and multidisciplinary exams.

SWE-bench (Coding)Score % / Points
Claude Haiku 4.5
73.3
DeepSeek V4 Pro 0813
—
Inference Economics & Cost Simulator

Token Pricing & Scale Economics

Calculate estimated monthly cloud API spend and evaluate the breakeven point vs self-hosted GPU hardware.

10k500k1M
Pricing MetricClaude Haiku 4.5DeepSeek V4 Pro 0813
Input Cost (/1M tokens)$1.00$1.32
Cached Input (/1M tokens)——
Output Cost (/1M tokens)$5.00$3.96
Simulated Monthly Bill (100,000 calls)
$250.00
~$2.50 / 1k queries
$250.80
~$2.51 / 1k queries
Self-Hosted Breakeven vs $864/mo GPUCloud API is more cost effectiveCloud API is more cost effective

Architecture Matrix

FeatureClaude Haiku 4.5DeepSeek V4 Pro 0813
Release Date10/15/20258/12/2026
Routing / MoEDenseDense
Attention MechanismStandard / GQAStandard / GQA
Source TypeProprietary Commercial APIOpen Weights (MIT)
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