Best value GPU for local LLMs in Europe (tok/s per euro)
Which card gives the most measured generation speed for each euro, at today's German retail prices? We divide real tokens/sec from sourced benchmarks by the lowest new price on billiger.de (incl. VAT, approx. price as of 2026-10-16).
value = measured tok/s ÷ GPU price (€) × 100 = tokens/sec you get per €100 of GPU. Higher is better. Where a source reports a range, we use the low end. GPU price only: CPU, RAM, PSU and case are not included. Used cards are often much cheaper.Top value pick per model
| Model | Best tok/s per euro | Fastest measured |
|---|---|---|
| gpt-oss 20B | RTX 3060†: 19.6 tok/s per €100 (83.96 tok/s, ≈€429) | RTX 5090: 313 tok/s (≈€6,199) |
| Gemma 4 12B | RTX 3060: 9.0 tok/s per €100 (38.5 tok/s, ≈€429) | RTX 5090: 142 tok/s (≈€6,199) |
| Qwen3.6 27B | RTX 5090: 1.2 tok/s per €100 (75.7 tok/s, ≈€6,199) | RTX 5090: 75.7 tok/s (≈€6,199) |
| Gemma 4 31B | RTX 5090: 1.1 tok/s per €100 (70.0 tok/s, ≈€6,199) | RTX 5090: 70.0 tok/s (≈€6,199) |
| Gemma 4 26B-A4B | RTX 4090: 4.1 tok/s per €100 (164 tok/s, ≈€3,955) | RTX 5090: 235 tok/s (≈€6,199) |
| Qwen3.5 9B | RTX 4090: 3.5 tok/s per €100 (137 tok/s, ≈€3,955) | RTX 5090: 208 tok/s (≈€6,199) |
| LFM2.5 24B-A2B | RTX 3060†: 29.1 tok/s per €100 (125 tok/s, ≈€429) | RTX 4090: 261-339 tok/s (≈€3,955) |
Speeds differ in quant, engine and context length between sources (shown in each row), so treat small gaps as noise and look at the order of magnitude. Every row links its build page and original source. † = model is bigger than the card's VRAM at Q4_K_M, see the note under that model's table.
gpt-oss 20B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 3060 | 12 | 83.96 llama.cpp | ≈€429 | 19.6 † | €5.1 | build · source |
| RTX 5070 Ti | 16 | 189.45 llama.cpp, MXFP4 | ≈€1,188 | 15.9 | €6.3 | build · source |
| RTX 5060 Ti 16GB | 16 | 111.51 llama.cpp, MXFP4 | ≈€739 | 15.1 | €6.6 | build · source |
| RTX 5080 | 16 | 204.85 llama.cpp, MXFP4 | ≈€1,599 | 12.8 | €7.8 | build · source |
| Radeon AI Pro R9700 | 32 | 163.26 llama.cpp | ≈€1,718 | 9.5 | €10.5 | build · source |
| RTX A4000 | 16 | 93.55 llama.cpp | ≈€1,050 | 8.9 | €11.2 | build · source |
| RTX 4090 | 24 | 279.65 llama.cpp | ≈€3,955 | 7.1 | €14.1 | build · source |
| RTX 4090 | 24 | 203 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 5.1 | €19.5 | build · source |
| RTX 5090 | 32 | 313 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 5.0 | €19.8 | build · source |
| RTX 5090 | 32 | 282.51 llama.cpp, MXFP4 | ≈€6,199 | 4.6 | €21.9 | build · source |
† gpt-oss 20B weights are about 13.0 GB at Q4_K_M / native size, more than this card's VRAM. The source may have used a smaller quant or partial CPU offload; check it before buying.
All measured speeds for gpt-oss 20B: best rig for gpt-oss 20B.
Gemma 4 12B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 3060 | 12 | 38.5 llama.cpp, llama-bench tg128 (quant per result) | ≈€429 | 9.0 | €11.1 | build · source |
| RTX 5070 Ti | 16 | 87.6 llama.cpp, llama-bench tg128 (quant per result) | ≈€1,188 | 7.4 | €13.6 | build · source |
| RTX 4090 | 24 | 98.1 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 2.5 | €40.3 | build · source |
| RTX 5090 | 32 | 142 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 2.3 | €43.7 | build · source |
All measured speeds for Gemma 4 12B: best rig for Gemma 4 12B.
Qwen3.6 27B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 5090 | 32 | 75.7 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 1.2 | €81.9 | build · source |
| RTX 4090 | 24 | 47.0 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 1.2 | €84.1 | build · source |
All measured speeds for Qwen3.6 27B: best rig for Qwen3.6 27B.
Gemma 4 31B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 5090 | 32 | 70.0 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 1.1 | €88.6 | build · source |
| RTX 4090 | 24 | 43.8 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 1.1 | €90.3 | build · source |
All measured speeds for Gemma 4 31B: best rig for Gemma 4 31B.
Gemma 4 26B-A4B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 4090 | 24 | 164 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 4.1 | €24.1 | build · source |
| RTX 5090 | 32 | 235 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 3.8 | €26.4 | build · source |
All measured speeds for Gemma 4 26B-A4B: best rig for Gemma 4 26B-A4B.
Qwen3.5 9B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 4090 | 24 | 137 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 3.5 | €28.9 | build · source |
| RTX 5090 | 32 | 208 llama.cpp, llama-bench tg128 (quant per result) | ≈€6,199 | 3.4 | €29.8 | build · source |
All measured speeds for Qwen3.5 9B: best rig for Qwen3.5 9B.
LFM2.5 24B-A2B: tokens/sec per euro
| GPU | VRAM GB | Measured tok/s | GPU price DE (new) | tok/s per €100 | € per tok/s | |
|---|---|---|---|---|---|---|
| RTX 3060 | 12 | 125 llama.cpp, llama-bench tg128 (quant per result) | ≈€429 | 29.1 † | €3.4 | build · source |
| RTX 4090 | 24 | 261-339 llama.cpp, llama-bench tg128 (quant per result) | ≈€3,955 | 6.6 | €15.2 | build · source |
† LFM2.5 24B-A2B weights are about 14.7 GB at Q4_K_M / native size, more than this card's VRAM. The source may have used a smaller quant or partial CPU offload; check it before buying.
All measured speeds for LFM2.5 24B-A2B: best rig for LFM2.5 24B-A2B.
Complete systems with a reported price
Laptops, Macs and full builds where the source states what the whole machine cost (converted to € at the ECB rate 1.1208 where needed).
| System | Model | tok/s | Reported price | tok/s per €100 |
|---|---|---|---|---|
| HP OmniBook Ultra 16 (RTX Spark N1X, 128GB) laptop: local AI benchmarks | Qwen3.6 35B-A3B | 89.5 | $6,230 (≈€5,559) | 1.6 |
| HP OmniBook Ultra 16 (RTX Spark N1X, 128GB) laptop: local AI benchmarks | gpt-oss 20B | 58.0 | $6,230 (≈€5,559) | 1.0 |
| $2K EPYC 64-core, 512 GB DDR4, CPU-only | DeepSeek R1 671B | 4.31 | $2,000 (≈€1,784) | 0.2 |
Not in the tables
- RTX 3090: no longer sold new in Germany, so there's no comparable new price. On the used market it's often the value king for 24 GB, see the used 3090 buying guide.
- Macs, Strix Halo, DGX Spark, RTX Spark: the GPU can't be bought separately; see Mac vs PC and the system table above.
- Cards with no measured 2026-model result in RigBase yet. Submit yours.
Next steps: check the model fits with the VRAM calculator, compare raw speed in best GPU for local LLMs 2026, or browse rigs by budget.
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