DeepSeek V3 0324
MoE
workstation
671B total, 37B active per token. Q4_K_M requires ~360GB RAM/VRAM. Use Q2_K (~180GB) for DGX Spark.
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Provider transparency docs →
coding
reasoning
- Parameters
-
671.0B
- Context
- 128k
- License
- mit
- Origin
-
🇨🇳
China
- Released
- Mar 2025
Run it locally
Per-quant memory needs and a static "can you run it?" reference - no rig entry required
Q2_K
188.0GB
188.0GB min
210.0GB rec
Smallest footprint, noticeable quality loss
Q4_K_M
368.0GB
368.0GB min
400.0GB rec
Balanced - the usual local sweet spot
The reference hardware
22 reference configs, drawn in-house. Scroll for more.
Can you run it? - reference rigs
Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.
Or run it in the cloud
Live per-provider pricing, throughput and uptime - refreshed about 19 hours ago via OpenRouter. Click a column to sort.
|
Provider
|
Type
|
Input $/M
|
Output $/M
|
Cache $/M
|
Tok/s
|
Latency
|
Uptime
|
Value
|
|
SiliconFlow
|
API
|
0.25 |
1.00 |
0.110 |
- |
- |
100.00% |
best uptime
|
|
GMICloud
avoid
|
API
|
0.29 |
1.14 |
0.110 |
- |
- |
60.00% |
|
Default order: throughput among 95%+ uptime providers, then latency; subscriptions last. Sort by any column. Subscription rows show $/mo in the Value column - per-token columns are "-". Affiliate links are marked sponsored / nofollow. Confirm current pricing on the provider's site before committing.
PRICE HISTORY
Inference cost over time
Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.
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