Fix RTX 8000 pricing: $2,000-2,900 realistic, not $750
The $750 listing was a single outlier. Actual market price for Quadro RTX 8000 Passive 48GB is $2,000-2,900 on eBay. Updated all recommendations and cost comparisons accordingly. https://claude.ai/code/session_01PtYTPherSJaxDEVPgF6Nxu
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@@ -41,19 +41,20 @@ Best strategy: use local models for routine tasks, save Claude credits for hard
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| GPU | Arch | Used Price | TDP | Cooling | Tensor Cores | Mem BW |
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|-----|------|------------|-----|---------|--------------|--------|
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| **Quadro RTX 8000** | Turing (2018) | **$750–1,400** | 260W | Passive variant | Yes (576) | 672 GB/s |
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| **Quadro RTX 8000** | Turing (2018) | **$2,000–2,900** | 260W | Passive variant | Yes (576) | 672 GB/s |
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| **A40** | Ampere (2020) | **~$5,050+** | 300W | Passive | Yes (336 3rd-gen) | 696 GB/s |
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| **RTX A6000** | Ampere (2020) | **~$5,400+** | 300W | Active (blower) | Yes (336 3rd-gen) | 768 GB/s |
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| **L40** | Ada (2022) | **~$6,500+** | 300W | Passive | Yes (568 4th-gen) | 864 GB/s |
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| **RTX 6000 Ada** | Ada (2022) | **~$6,500+** | 300W | Active | Yes (568 4th-gen) | 960 GB/s |
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Sources: eBay active/sold listings, GPUPoet price tracking, Pangoly, CamelCamelCamel (all March 2026)
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Note: One outlier RTX 8000 listing at ~$750 exists but is not representative of the market.
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### Winner: Quadro RTX 8000 Passive ($750–1,400)
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### Cheapest 48GB Option: Quadro RTX 8000 Passive ($2,000–2,900)
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The RTX 8000 is **4–5x cheaper** than every other 48GB option. The passive variant is
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purpose-built for rack servers — no fan, relies on chassis airflow, designed for 24/7 operation
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in 2U/4U systems.
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The RTX 8000 is still the cheapest 48GB card — roughly half the price of an A40 and a
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third of an A6000. The passive variant is purpose-built for rack servers — no fan, relies
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on chassis airflow, designed for 24/7 operation in 2U/4U systems.
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Key advantages over the P40:
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- **48GB vs 24GB** — room for models + massive context
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@@ -61,6 +62,16 @@ Key advantages over the P40:
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- **NVLink support** — pair two for 96GB combined (100 GB/s bidirectional)
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- 10W idle power draw
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### Cost Reality Check
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At $2,000–2,900 the RTX 8000 is a significant investment. The key question: is unified
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48GB VRAM worth 4–6x the cost of dual P40s ($400–500)?
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**Yes, if** you need large context windows (32K+) for complex coding — KV cache can't
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be split across two GPUs without NVLink (which P40s don't have).
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**No, if** you're mostly doing short-prompt coding tasks and image gen — dual P40s give
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you 48GB total (split) at a fraction of the cost, and each card can handle its own workload.
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## RTX 8000 Performance Benchmarks
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### LLM Inference (Exllama, 5.0 bpw quantization)
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@@ -77,6 +88,7 @@ Key advantages over the P40:
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| Metric | P40 (24GB) | RTX 8000 (48GB) |
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|--------|-----------|-----------------|
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| **Used price** | **$150–320** | **$2,000–2,900** |
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| 32B model fit | Barely (~2GB free) | Comfortable (~28GB free) |
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| 32B generation speed | ~5-12 t/s (est.) | ~20-34 t/s |
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| Max practical context | ~4K tokens | **32K+ tokens** |
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@@ -128,21 +140,22 @@ though still behind Ampere/Ada cards.
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## Recommended Setups
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### Best Overall: RTX 8000 Passive ($750–1,400)
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### If budget allows ($2,000–2,900): RTX 8000 Passive
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Single card handles both coding and image gen. 48GB VRAM fits 32B models with massive
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context windows. Passive cooling is rack-native. Tensor cores handle FP16 image gen properly.
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One card, one slot, simple setup.
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context windows (32K+). Passive cooling is rack-native. Tensor cores handle FP16 image gen
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properly. One card, one slot, simple setup. The premium buys you unified VRAM = big context.
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### Best Overall + Dedicated Image Gen: RTX 8000 + A2000 ($1,000–1,750)
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### If budget allows + dedicated image gen ($2,300–3,250): RTX 8000 + A2000
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RTX 8000 for coding with full 48GB dedicated to LLM context.
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A2000 for image gen (3x faster than Turing, 70W, bus-powered, blower cooled).
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Best separation of concerns — no model swapping needed.
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### Budget Alternative: Dual P40 ($400–500)
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### Best value ($400–500): Dual P40
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Two P40s for 48GB total, but split across cards (can't combine for one model without
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tensor parallelism). One for 32B coding (tight fit), one for image gen (slow, needs --force-fp32).
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NVLink, which P40s lack). One for 32B coding (tight fit, ~4K context), one for image gen
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(slow, needs --force-fp32). **5x cheaper than RTX 8000** but with significant context limitations.
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### Cheapest Entry: Single P40 ($200–300)
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### Cheapest entry ($200–300): Single P40
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Run 32B coding model with very limited context (~4K tokens). Swap to image gen when needed.
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Good for testing whether local LLM coding works for your workflow before investing more.
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