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Modelldaten

Sieh, welche Modelle echte Nutzung gewinnen, wie sich der Mix verschiebt und was das für die Kosten bedeutet.

Stand 13. November 2026: DeepSeek V4.1 Flash lag in den letzten 7 Tagen bei der OpenCode-Nutzung mit 167T Tokens vorn, gefolgt von GLM-5.3-Flash (8T) und MiniMax-M3.1-Flash (7.3T).

Top-Modelle. Nutzung von Modellen in OpenCode.

Gestapeltes Nutzungsdiagramm der Top-Modelle
Datumdeepseek-v4.1-flashglm-5.3-flashminimax-m3.1-flashmuse-spark-1.3-contributorbeam-1.0-501b-a23binkling-2-smallmimo-v2.6-flashnemotron-3.5-super-vldeepseek-v4.1-flash-1017Othergesamt
SEP 196.5T380B0B4.7T0B0B0B0B0B4.6T16T
SEP 206.9T426B0B4.8T0B0B0B0B0B4.7T17T
SEP 218.9T566B0B5.4T0B0B32B0B0B5.4T20T
SEP 228.0T506B0B5.7T0B0B941B0B0B5.3T20T
SEP 237.0T446B1.5T5.8T0B0B1.2T0B0B4.6T21T
SEP 246.2T402B6.8T5.4T0B0B1.2T0B0B4.5T25T
SEP 254.6T370B9.0T5.1T0B0B1.3T0B0B3.4T24T
SEP 264.3T309B7.9T5.1T0B0B1.2T0B0B2.5T21T
SEP 274.4T299B8.3T5.1T0B0B1.2T0B0B2.5T22T
SEP 286.3T413B8.7T5.5T0B0B1.5T0B0B3.5T26T
SEP 296.5T408B9.6T5.3T0B0B1.5T0B0B3.1T26T
SEP 305.8T389B10T4.8T0B0B1.5T0B0B2.9T25T
OCT 15.0T300B9.7T4.6T0B0B1.4T0B0B2.4T23T
OCT 24.9T277B9.0T4.4T0B0B1.4T0B0B2.5T22T
OCT 34.5T245B8.3T5.0T0B0B1.3T0B0B2.3T22T
OCT 44.6T253B8.9T5.2T0B0B1.3T0B0B2.4T23T
OCT 55.6T327B9.9T5.8T0B0B1.5T0B0B2.6T26T
OCT 66.0T335B5.8T6.1T0B0B2.2T0B0B3.1T24T
OCT 75.9T361B3.9T5.8T0B0B2.4T0B0B3.2T22T
OCT 86.6T381B3.7T5.9T0B0B2.4T0B0B3.4T22T
OCT 97.4T391B3.5T5.6T0B0B1.8T0B0B3.9T23T
OCT 107.3T352B3.3T5.8T0B0B1.5T0B0B4.0T22T
OCT 116.7T317B3.0T5.8T0B0B1.3T0B0B3.5T21T
OCT 129.4T485B3.1T5.9T0B0B1.6T0B0B3.4T24T
OCT 1311T462B3.1T6.1T135B0B1.6T0B0B3.3T26T
OCT 1411T474B3.0T6.1T340B0B1.6T0B0B3.0T26T
OCT 1513T489B2.9T5.7T330B0B1.8T87B0B2.7T27T
OCT 1615T758B2.5T5.3T427B0B1.6T293B0B1.6T27T
OCT 1714T1.4T2.6T1.2T836B0B1.3T374B0B1.2T23T
OCT 1813T1.2T2.2T1.1T761B0B1.4T334B0B1.5T22T
OCT 1918T1.5T4.7T1.3T822B0B1.7T335B71B1.9T30T
OCT 2019T1.5T10T1.2T679B0B1.6T331B22B2.0T37T
OCT 2119T1.4T14T1.1T626B0B1.2T307B25B1.8T40T
OCT 2218T1.5T7.5T1.1T817B0B933B291B388B1.6T32T
OCT 2318T1.4T162B1.1T1.0T0B815B279B551B1.5T24T
OCT 2415T833B121B1.0T722B0B517B140B6B1.5T19T
OCT 2516T910B98B975B762B0B571B148B394B1.4T21T
OCT 2620T1.1T133B1.2T849B0B715B137B803B1.3T26T
OCT 2721T1.2T120B1.2T870B0B678B223B164B1.6T27T
OCT 2822T1.1T109B1.2T859B0B648B221B0B1.7T27T
OCT 2920T1.0T100B1.1T893B0B604B169B84B1.3T26T
OCT 3019T933B90B1.1T926B0B576B130B143B1.4T24T
OCT 3118T838B74B972B883B0B473B139B144B1.3T23T
NOV 119T836B67B928B884B0B416B137B127B1.2T23T
NOV 224T1.0T104B1.1T914B0B508B159B67B1.6T29T
NOV 327T1.0T101B1.1T859B0B520B142B93B1.7T32T
NOV 426T1.1T94B1.0T812B0B552B387B137B1.6T32T
NOV 525T1.1T96B1.0T834B0B543B535B114B1.7T31T
NOV 623T1.1T88B1.0T846B0B574B505B67B2.1T29T
NOV 718T1.0T80B881B754B340B471B484B76B1.4T23T
NOV 821T972B67B802B729B531B440B514B206B1.5T27T
NOV 928T1.2T102B998B794B596B498B531B258B2.0T35T
NOV 1029T1.3T1.3T1.0T871B731B528B527B257B1.7T37T
NOV 1126T1.4T2.3T973B835B814B548B402B379B1.5T36T
NOV 1228T1.3T2.7T923B877B963B516B207B284B1.3T37T
NOV 1317T807B770B403B473B608B290B98B114B751B21T
01
deepseek-v4.1-flash167T Tokens
DeepSeek+3% ggü. Vorwoche
02
glm-5.3-flash8.0T Tokens
Zhipu+14% ggü. Vorwoche
03
minimax-m3.1-flash7.3T Tokens
MiniMaxNeu
04
muse-spark-1.3-contributor6.0T Tokens
Meta-15% ggü. Vorwoche
05
beam-1.0-501b-a23b5.3T Tokens
Reflection-12% ggü. Vorwoche
06
inkling-2-small4.6T Tokens
Thinking MachinesNeu
07
mimo-v2.6-flash3.3T Tokens
Xiaomi-8% ggü. Vorwoche
08
nemotron-3.5-super-vl2.8T Tokens
NVIDIA+38% ggü. Vorwoche
09
deepseek-v4.1-flash-10171.6T Tokens
DeepSeek+110% ggü. Vorwoche
10
muse-ember-1.01.4T Tokens
Meta+63% ggü. Vorwoche
11
gpt-6-luna976B Tokens
OpenAI-12% ggü. Vorwoche
12
deepseek-v4-pro958B Tokens
DeepSeek+1% ggü. Vorwoche
13
deepseek-v4.1-flash-1017-op819B Tokens
DeepSeek-22% ggü. Vorwoche
14
iceman657B Tokens
+85% ggü. Vorwoche
15
nemotron-3.5-lightning626B Tokens
NVIDIA-8% ggü. Vorwoche
16
glm-5.3590B Tokens
Zhipu+148% ggü. Vorwoche
17
longcat-2.5478B Tokens
MeituanNeu
18
flint-40b467B Tokens
Recursive-27% ggü. Vorwoche
MEHR ERFAHRENTOP-MODELLE▸

Eindeutige Nutzer. Täglich eindeutige OpenCode-Nutzer nach Modell.

Gestapeltes Diagramm eindeutiger Nutzer nach Modell
Datumdeepseek-v4.1-flashgpt-6-lunaglm-5.3-flashmimo-v2.6-flashbeam-1.0-501b-a23bdeepseek-v4-promuse-spark-1.3-contributorclaude-haiku-5-5glm-5.3Othergesamt
SEP 1953K015K006.7K28K04.4K126K234K
SEP 2054K016K006.9K25K04.5K117K223K
SEP 2180K021K2.2K09.6K38K06.0K163K320K
SEP 2266K019K41K08.2K36K05.6K156K333K
SEP 2362K2.5K18K39K07.4K35K04.7K140K308K
SEP 2460K12K16K37K06.8K34K04.3K136K306K
SEP 2549K12K13K21K05.8K32K03.6K123K260K
SEP 2645K11K12K18K04.9K29K03.2K109K231K
SEP 2746K12K12K17K04.8K28K03.4K110K233K
SEP 2862K16K15K22K07.1K34K04.9K145K307K
SEP 2968K17K15K23K07.1K36K05.0K146K317K
SEP 3061K16K15K22K06.6K34K04.8K141K301K
OCT 156K15K13K22K05.9K33K04.3K128K277K
OCT 254K15K13K22K05.7K32K04.2K126K271K
OCT 346K13K11K18K04.5K29K03.6K112K236K
OCT 445K13K11K17K04.5K29K03.5K111K234K
OCT 554K17K13K21K06.1K35K04.7K134K284K
OCT 658K17K14K41K06.2K38K04.7K136K315K
OCT 765K18K14K42K06.2K39K6914.6K133K321K
OCT 874K20K15K42K06.7K37K4.9K5.0K143K347K
OCT 988K20K15K31K06.4K35K5.4K4.8K136K341K
OCT 1080K17K13K28K05.3K31K4.8K4.3K123K307K
OCT 1173K16K11K22K04.8K31K4.4K3.9K111K278K
OCT 1299K24K16K29K06.7K37K6.5K5.4K137K360K
OCT 13102K26K16K27K6.7K7.1K37K6.3K5.5K133K367K
OCT 14107K28K16K32K11K7.6K36K6.3K5.6K126K376K
OCT 15123K29K17K42K8.9K8.1K35K6.6K5.9K124K399K
OCT 16128K27K27K42K11K7.5K34K5.8K5.6K119K408K
OCT 17121K24K31K39K14K6.3K11K4.9K4.5K105K359K
OCT 1898K21K23K28K12K5.4K7.9K4.2K3.8K79K282K
OCT 19137K32K30K36K13K7.8K9.8K6.2K5.5K111K388K
OCT 20142K33K30K35K12K7.5K9.3K6.1K5.5K113K393K
OCT 21144K34K32K27K12K7.7K9.4K6.2K5.9K134K412K
OCT 22149K34K32K24K14K7.7K9.4K6.3K5.4K130K411K
OCT 23152K34K32K22K16K7.2K9.7K6.0K5.1K96K379K
OCT 24122K28K25K14K13K5.8K8.2K5.0K4.3K77K303K
OCT 25116K29K24K14K13K5.8K7.9K5.1K4.1K76K296K
OCT 26147K40K30K18K15K8.4K9.8K6.9K5.7K93K374K
OCT 27154K42K31K18K16K8.9K9.8K7.1K5.7K85K378K
OCT 28158K42K30K18K15K8.7K9.8K7.3K5.3K79K374K
OCT 29161K42K31K18K16K8.7K9.7K7.3K5.3K74K373K
OCT 30153K40K29K17K16K7.8K9.3K6.9K5.1K73K357K
OCT 31130K33K24K14K15K6.5K7.9K5.9K4.3K64K305K
NOV 1129K33K24K14K14K6.6K7.4K5.8K4.3K62K301K
NOV 2173K46K31K17K16K9.2K9.1K8.4K5.8K85K401K
NOV 3180K48K32K17K17K9.5K9.4K8.7K5.8K75K402K
NOV 4185K47K32K17K16K9.0K9.2K8.5K5.6K79K409K
NOV 5190K48K34K17K17K9.4K9.4K8.8K5.8K81K420K
NOV 6187K46K36K17K16K9.6K9.3K8.4K5.8K78K414K
NOV 7159K37K32K15K14K7.7K8.4K7.1K4.8K71K357K
NOV 8151K35K28K13K14K6.8K7.5K6.3K4.4K73K339K
NOV 9189K49K35K16K15K9.6K9.1K8.8K6.2K92K431K
NOV 10193K50K36K16K16K9.8K9.3K9.1K13K93K446K
NOV 11190K49K38K16K16K10.0K9.2K8.8K14K94K445K
NOV 12198K49K36K15K15K9.1K8.9K8.6K5.3K86K430K
NOV 13164K34K26K11K11K6.2K6.9K6.0K3.6K59K328K

Weekly Retention. Weekly users returning the next week.

RankModelRetentionRateEligible
01mimo-v2.6-flash80.2%9.6K
02deepseek-v4.1-flash75.6%637K
03beam-1.0-501b-a23b74.5%7.9K
04minimax-m3.1-flash72.2%15K
05muse-spark-1.3-contributor69.2%55K
06mimo-v2.6-pro68.2%8.1K
07iceman-contributor67.8%423
08gpt-6-luna66.7%17K
09claude-haiku-5-566.1%7.7K
10gemini-4-argon64.9%1.9K
11hy364.1%1.1K
12minimax-m2.563.3%109
13glm-5.3-flash62.7%68K
14qwen3.8-flash61.6%9.2K
15qwen3.7-plus61.3%5.6K
MEHR ERFAHRENTOP-MODELLE▸

Sitzungskosten. Durchschnittliche Kosten pro Sitzung.

KOSTEN / SITZUNG

TOKENS / SITZUNG

Kosten/Sitzung$0.0278

Tokens/Sitzung15.6M

MEHR ERFAHRENSITZUNGSKOSTEN▸

Tokenkosten. Preis pro 1 Mio. Tokens.

Eingabe$0.12

Ausgabe$0.42

Gecacht$0.03

MEHR ERFAHRENTOKENKOSTEN▸

Cache-Anteil. Anteil der Eingabetokens, die aus dem Cache bedient wurden.

Cache-Anteil97%

Gecacht5.8T

Nicht gecacht183.2B

MEHR ERFAHRENCACHE-ANTEIL▸

Marktanteil. Vergleiche den Tokenanteil nach Modellautor.

Marktanteil nach Modellautor
DatumDeepSeekMiniMaxMetaXiaomiZhipuOtherNVIDIAReflectionMeituan
SEP 1955.4%0.2%31.7%4.9%2.5%1.9%3.4%0.0%0.0%
SEP 2056.3%0.2%30.8%4.9%2.7%1.8%3.2%0.0%0.0%
SEP 2158.3%0.2%29.1%4.9%3.0%1.9%2.6%0.0%0.0%
SEP 2254.3%0.2%29.9%8.5%2.7%1.7%2.7%0.0%0.0%
SEP 2348.4%7.4%30.7%7.8%2.3%1.6%1.7%0.0%0.0%
SEP 2437.1%28.0%23.9%6.0%1.8%1.4%1.8%0.0%0.0%
SEP 2527.0%37.9%22.6%6.6%1.7%1.4%2.8%0.0%0.0%
SEP 2624.7%37.1%24.5%6.6%1.5%1.4%3.6%0.0%0.7%
SEP 2723.9%38.1%23.8%6.5%1.5%1.3%3.2%0.0%1.7%
SEP 2830.0%33.8%21.6%6.7%1.7%1.4%2.7%0.0%2.1%
SEP 2929.8%36.5%20.4%6.6%1.7%1.1%1.9%0.0%2.1%
SEP 3027.5%39.8%19.2%6.7%1.7%1.0%1.9%0.0%2.2%
OCT 125.0%41.7%19.9%6.8%1.4%1.0%2.4%0.0%1.8%
OCT 225.4%40.1%20.1%7.2%1.4%1.8%2.6%0.0%1.4%
OCT 323.8%38.5%23.2%6.9%1.2%2.2%2.9%0.0%1.4%
OCT 422.9%39.3%23.2%6.6%1.2%2.2%3.2%0.0%1.2%
OCT 524.5%38.7%22.8%6.6%1.4%2.4%2.5%0.0%1.1%
OCT 630.0%24.7%26.1%10.3%1.6%3.2%2.5%0.0%1.6%
OCT 732.8%18.2%27.2%11.8%1.8%3.3%3.1%0.0%1.7%
OCT 834.5%16.7%26.6%11.6%1.9%4.2%3.0%0.0%1.6%
OCT 937.5%15.8%25.0%8.4%1.9%6.6%3.3%0.0%1.6%
OCT 1036.9%15.1%26.1%7.4%1.7%7.8%3.5%0.0%1.4%
OCT 1136.1%14.6%28.4%6.9%1.7%7.0%4.1%0.0%1.3%
OCT 1243.2%13.2%25.0%7.5%2.2%4.1%3.6%0.0%1.2%
OCT 1345.7%12.4%24.1%7.0%2.0%4.1%3.2%0.5%1.0%
OCT 1445.4%11.8%23.8%6.9%2.0%4.3%3.2%1.3%1.3%
OCT 1548.8%11.0%21.5%7.3%2.0%4.1%2.7%1.2%1.4%
OCT 1655.3%9.2%19.5%6.6%2.9%2.2%1.4%1.6%1.4%
OCT 1762.3%11.4%5.4%6.0%6.3%1.3%2.0%3.7%1.7%
OCT 1861.6%10.4%5.1%7.1%5.5%1.2%4.0%3.5%1.5%
OCT 1960.8%15.6%4.3%6.1%5.1%1.3%3.1%2.7%1.1%
OCT 2053.2%28.1%3.3%4.6%4.2%1.0%2.9%1.8%0.9%
OCT 2148.2%36.3%2.7%3.4%3.7%0.9%2.8%1.6%0.4%
OCT 2258.3%23.3%3.5%3.3%4.8%1.1%3.2%2.5%0.0%
OCT 2375.4%0.8%4.7%3.9%5.7%1.5%3.7%4.2%0.1%
OCT 2476.0%0.9%5.3%3.3%4.5%3.9%2.3%3.7%0.2%
OCT 2577.8%0.7%4.7%3.4%4.5%2.9%2.2%3.7%0.1%
OCT 2679.9%0.8%4.7%3.4%4.6%2.5%0.8%3.3%0.1%
OCT 2779.3%0.7%4.5%3.1%4.4%3.8%1.1%3.2%0.0%
OCT 2879.8%0.6%4.3%2.9%4.1%4.1%1.0%3.1%0.0%
OCT 2980.7%0.6%4.4%2.7%4.2%2.9%1.0%3.5%0.0%
OCT 3080.7%0.6%4.6%2.7%4.0%2.7%0.9%3.8%0.0%
OCT 3181.8%0.5%4.3%2.3%3.8%2.5%1.0%3.8%0.0%
NOV 182.5%0.4%4.0%2.0%3.7%2.5%0.9%3.8%0.0%
NOV 283.4%0.5%3.7%2.0%3.7%2.7%0.9%3.1%0.0%
NOV 384.1%0.5%3.5%1.8%3.4%3.4%0.7%2.7%0.0%
NOV 483.5%0.4%3.4%1.9%3.4%3.3%1.6%2.5%0.0%
NOV 582.0%0.5%3.7%1.9%3.6%3.5%2.1%2.7%0.0%
NOV 679.4%0.4%5.7%2.2%4.0%3.4%2.1%2.9%0.0%
NOV 777.3%0.5%5.7%2.2%4.6%3.9%2.5%3.2%0.0%
NOV 880.5%0.4%4.6%1.8%3.7%4.1%2.2%2.7%0.0%
NOV 981.7%0.4%4.3%1.7%3.6%3.9%1.8%2.3%0.3%
NOV 1079.3%3.5%2.9%1.6%4.1%3.8%1.7%2.4%0.7%
NOV 1176.3%6.5%2.8%1.7%4.5%4.2%1.4%2.4%0.2%
NOV 1277.1%7.4%2.5%1.6%3.7%4.4%0.8%2.4%0.2%
NOV 1380.9%3.7%1.9%1.5%3.9%4.7%0.8%2.2%0.2%
  1. 01DeepSeek17T Tokens80.9%
  3. 03Zhipu831B Tokens3.9%
  4. 04MiniMax790B Tokens3.7%
  5. 05Reflection473B Tokens2.2%
  6. 06Meta408B Tokens1.9%
  7. 07Xiaomi323B Tokens1.5%
  8. 08NVIDIA167B Tokens0.8%
  9. 09Meituan45B Tokens0.2%

[*]NOV 13 2026

MEHR ERFAHRENMARKTANTEIL▸

Geografische Aufschlüsselung

MEHR ERFAHRENGEOGRAFISCHE AUFSCHLÜSSELUNG▸

Methodik. So werden diese Daten erhoben.

Aktualisierungen
Stündlich aggregiert. Tage und Wochen basieren auf UTC.
Tokens
Eingabe-, Ausgabe-, Reasoning- und gecachte Tokens jeder Anfrage.
Nutzer und Sitzungen
Ungefähre Anzahl eindeutiger Nutzer und OpenCode-Sitzungen.
Kosten
Sitzungskosten sind die durchschnittlichen Kosten pro OpenCode-Sitzung. Tokenpreise sind Listenpreise aus dem OpenCode-Modellkatalog.
Nutzerbindung
Der Anteil der Nutzer eines Modells in einer Woche, die es in der folgenden Woche erneut nutzen.
Zitieren
Zitiere OpenCode Data (opencode.ai/data) mit der oben auf der Seite angezeigten Aktualisierungszeit.

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