Best AI models for web search for a 16GB graphics card
A leaderboard of the best AI models for web search for a 16GB graphics card (with 32GB of system RAM). The best one that runs on it right now is Mistral Small 3.1 24B (2503). Models are ranked on web research tests like BrowseComp, with search turned on. Models that run on it show the download that fits and the command to run it.
Scores use reviewed web search evaluations only. Compare scores within this task. Models without task measurements are excluded.
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Score vs API price
● open weights ◆ API only ─┘ best score for the price · x: USD per 1M tokens, 3 input : 1 output (log)
| # | model | task score↓ | where↓ | speed↓ | sources |
|---|
| # | model | task score↓ | where↓ | speed↓ | sources |
|---|---|---|---|---|---|
| 2 | 92±2* | api $3.50/M | |||
| 3 | 87±2* | api $1.93/M | |||
| 5 | 79±3* | api $3.50/M | |||
| 7 | 75±3* | api $26.25/M | |||
| 8 | 74±3* | api $0.70/M | |||
| 9 | 74±3* | api $4.38/M | |||
| 11 | 67±5* | api $8.00/M | |||
| 13 | 65±3* | api $1.93/M | |||
| 14 | 63±4*† | api $20.00/M | |||
| 15 | 62±3* | api $0.26/M | |||
| 16 | 62±3* | local (slow) | |||
| 17 | 62±6*† | api $8.00/M | |||
| 18 | 62±4*† | api $4.50/M | |||
| 19 | 62±4*† | api $67.50/M | |||
| 20 | 62±4*† | api $67.50/M | |||
| 21 | 61±4*† | api $10.00/M | |||
| 22 | 60±6*† | api $20.00/M | |||
| 23 | 59±6*† | api $4.00/M | |||
| 24 | 58±4 | api $20.00/M | |||
| 25 | 58±4*† | limited preview | |||
| 26 | 57±4*† | api $0.45/M | |||
| 27 | 55±2 | api $11.25/M | |||
| 28 | 55±6* | api $10.00/M | |||
| 29 | 55±3 | api $5.63/M | |||
| 30 | 55±10* | api $1.56/M | |||
| 31 | 54±2 | api $10.00/M | |||
| 32 | 54±10* | api $3.00/M | |||
| 34 | 54±6*† | api $0.20/M | |||
| 35 | 53±4 | api $4.00/M | |||
| 36 | 53±5* | api $10.00/M | |||
| 37 | 52±3 | api $6.00/M | |||
| 38 | 52±10* | api $0.28/M | |||
| 39 | 52±4* | api $0.15/M +local | |||
| 40 | 52±4*† | api $4.81/M | |||
| 41 | 52±10* | api $1.13/M | |||
| 42 | 52±8*† | api $0.24/M | |||
| 43 | 51±10* | api $10.00/M | |||
| 44 | 51±6*† | api $1.30/M | |||
| 45 | 50±3 | api $2.15/M | |||
| 46 | 50±10* | api $3.44/M | |||
| 47 | 50±10* | api $3.44/M | |||
| 48 | 50±3* | api $3.38/M | |||
| 49 | 49±3* | api $0.48/M | |||
| 50 | 49±5* | api $4.38/M +local | |||
| 51 | 48±10* | api $6.00/M | |||
| 52 | 48±6*† | api $0.64/M +local | |||
| 54 | 47±3* | api $3.75/M | |||
| 55 | 46±2 | api $2.15/M | |||
| 56 | 46±6* | api $1.20/M +local | |||
| 57 | 45±3 | api $4.50/M | |||
| 58 | 45±10* | api $4.81/M | |||
| 61 | 44±3† | api $1.55/M | |||
| 62 | 43±6* | api $0.42/M | |||
| 64 | 42±6* | api $0.72/M +local | |||
| 65 | 42±3 | api $1.71/M | |||
| 66 | 42±6*† | api $41.25/M | |||
| 67 | 41±3† | api $1.10/M | |||
| 68 | 41±10* | api $3.44/M | |||
| 69 | 41±3 | api $1.09/M | |||
| 70 | 41±2 | api $1.69/M | |||
| 71 | 41±3† | api $0.84/M +local | |||
| 72 | 40±3* | api $1.56/M | |||
| 73 | 40±6* | api $0.17/M | |||
| 74 | 39±3† | api $0.35/M +local | |||
| 76 | 38±3 | api $0.19/M +local | |||
| 77 | 38±5* | api $0.53/M | |||
| 78 | 38±2† | api $1.00/M | |||
| 79 | 38±6*† | api $0.46/M | |||
| 82 | 34±4*† | api $1.35/M | |||
| 83 | 34±4* | api $0.31/M +local | |||
| 84 | 33±6*† | api $0.69/M | |||
| 85 | 31±3† | api $1.00/M | |||
| 86 | 31±5* | api $0.56/M | |||
| 88 | 23±8*† | api $0.14/M +local | |||
| 89 | 21±4*† | api $1.00/M | |||
| 90 | 20±6*† | api $2.00/M | |||
| 91 | 19±6*† | api $0.42/M +local | |||
| — | not yet calibrated | api $0.91/M | |||
| — | not yet calibrated | api $0.42/M | |||
| — | not yet calibrated | api $0.11/M | |||
| — | not yet calibrated | api $1.63/M | |||
| — | not yet calibrated | api $0.26/M | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not scored yet | api $0.0000/M +local | |||
| — | not yet calibrated | api $0.26/M | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | api $0.23/M | |||
| — | not yet calibrated | api $1.25/M | |||
| — | not yet calibrated | api $1.73/M | |||
| — | not yet calibrated | api $0.64/M | |||
| — | not scored yet | local | |||
| — | not yet calibrated | api $1.07/M | |||
| — | not yet calibrated | api $1.20/M | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | api $0.65/M | |||
| — | not yet calibrated | local | |||
| — | not scored yet | api $0.087/M +local | |||
| — | not yet calibrated | local | |||
| — | not scored yet | api $0.28/M | |||
| — | not yet calibrated | local (slow) | |||
| — | not yet calibrated | local (slow) | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | local | |||
| — | not yet calibrated | api $0.15/M |
+ 20 more don't fit your machine or budget · show them
+ 1 models with fewer than 3 results left off, since one or two tests say little about overall ability · show them
131 of 135 catalogue models listed here · sources and licences
* new or thinly tested: ranked on too few benchmark results · † only the maker’s own numbers so far · ~RAM is estimated; full context may need more memory