RISE Humanities Data Benchmark, 0.6.1

Search Test Runs

 

A test run is a single execution of a benchmark test using a defined model configuration.
Each run represents how a particular large language model (LLM) — such as GPT-4, Claude-3, or Gemini — performed on a given task at a specific time, with specific settings.

A test run includes:

  • Prompt and role definition – what the model was asked to do and from what perspective (e.g. “as a historian”).
  • Model configuration – provider, model version, temperature, and other generation parameters.
  • Results – the model’s actual response and its evaluation (scores such as F1 or accuracy).
  • Usage and cost data – token counts and calculated API costs.
  • Metadata – information like the test date, benchmark name, and person who executed it.

Together, test runs make it possible to compare models, providers, and configurations across benchmarks in a transparent and reproducible way.

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Search Results

Your search for Benchmark 'medieval_manuscripts__true' with Search Hidden 'False' returned 177 results, showing page 9 of 18.
Result 81 of 177

Test T1546 at 2026-08-16

manuscript transcription handwritten 15 de prose

huggingface thinkingmachines/Inkling-Small · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score23.1%
CER ↓77.7%

{"folios":[{"folio":"j","text":"Und ein praut Die mir und
minen freunden oder guisfend
Ich waß menny lang weg
Dame ich mir machend
und vilbant sie bracht gut
mir vil in vng an Sen ang
und Sie plerut vng in die
part und waß ze mol im grossen
nebel ich bin freudend
und als mir grossen arbeit kam
mir ze mittem tag zu sant
Enstoff uff. Sey bexey So
So frech ich die buche So far
ich frey wogen in ston
Die in stur Schwy gelben hand
So stund mich wacker Schwy
wogen doch in dem weg","addition1":"a","addition2":"b","addition3":""}]}

Scoring

Fuzzy score42.4%
CER ↓63.4%

Speed

Model time, all inputs1062.9 s
Mean per input88.58 s
Slowest input185.46 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens28K
Output tokens104K
Total tokens132.1K
Input cost$0.0126
Output cost$0.1249
Total cost$0.1375

Priced from 2026-08-15 · Input $/M $0.45 · Output $/M $1.20

Result 82 of 177

Test T1576 at 2026-08-16

manuscript transcription handwritten 15 de prose

huggingface meta-models/Muse-Glimmer-30B · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score89.3%
CER ↓10.8%

{"folios":[{"folio":"3","text":"Und ein pferit Sie wir und
minen Enckten vnder Aufsand
Den So was menen Eyn weg
Semme Den wir machten
und vichent Sie Enckte Suck
und vil in vntz an Sen anb
und Sie pferit vntz an Sie
petel und was ze mol ein groffer
nebel Es wir kum gespand
und als mit groffer arbait kome
wir ze mittrem tag zu Sant
Eripoffel vff Sen Berg So
So fach ich die Bücher So gar
vil Gerrin wopen in Rome
Sie in fir Ed Gyn gelben Gand
So pünt mines vatters Plagen
wopen aof in Sen emen","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score64.9%
CER ↓38.9%

Speed

Model time, all inputs824.7 s
Mean per input68.73 s
Slowest input300.47 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens49.7K
Output tokens57K
Total tokens106.7K
Input cost$0.0174
Output cost$0.0856
Total cost$0.1029

Priced from 2026-08-15 · Input $/M $0.35 · Output $/M $1.50

Result 83 of 177

Test T1531 at 2026-08-15

manuscript transcription handwritten 15 de prose

huggingface MiniMaxAI/MiniMax-M3 · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score91.5%
CER ↓8.7%

{"folios":[{"folio":"3","text":"vnd ein pꝛeit die wir vnd
vnsern knechten oder hulffend
sey So was nemen kün weg
denne das wir machtend
vnd richtend die knecht jnck
mit vil in vng an sey vnd
vnd die pꝛeit vng an die
ketel vnd was ze mol in grosser
not dz wir kum ge sadtend
vnd als mit grosser arbeite kame
wir ze mittem tag zu sant
fridpffel vff den berg do
do sach ich die brucken do gar
vil herren wopen in sone
die in feilr schin geberg gand
do stund minen vatterd klagend
wopen och in dem einen","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score70.4%
CER ↓33.2%

Speed

Model time, all inputs192.6 s
Mean per input16.05 s
Slowest input32.78 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens14.5K
Output tokens2.7K
Total tokens17.2K
Input cost$0.0041
Output cost$0.003
Total cost$0.007

Priced from 2026-08-15 · Input $/M $0.28 · Output $/M $1.10

Result 84 of 177

Test T1516 at 2026-08-15

manuscript transcription handwritten 15 de prose

huggingface Qwen/Qwen3-VL-235B-A22B-Instruct · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score93.1%
CER ↓6.9%

{"folios":[{"folio":"3","text":"Vnd ein pferit die wir vnd
minen knechten vber Rulfend
Gen do was menny ein Weg
Seme den wir machten
vnd vielend die knechte sich
vnd vil in vntz an den arb
vnd die pferit vnz an die
Petrel vnd was ze mot ein großer
nebel & wir kum gepaffen
vnd als mit großer arbeit kame
wir ze mitten tag zu Pant
Einstoffel vff den berg do
do fach ich die bucher do gar
vil herrin wopen in stone
Die ir stiur & gnu geben hand
do fand mineb vatterb flugen
wopen sich in dem smeg","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score68.0%
CER ↓33.3%

Speed

Model time, all inputs109.5 s
Mean per input9.12 s
Slowest input14.81 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens39.3K
Output tokens2.8K
Total tokens42.1K
Input cost$0.0079
Output cost$0.0025
Total cost$0.0103

Priced from 2026-08-15 · Input $/M $0.20 · Output $/M $0.88

Result 85 of 177

Test T1501 at 2026-08-14

manuscript transcription handwritten 15 de prose

huggingface swiss-ai/apertus-v1.5-8b · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score25.8%
CER ↓75.4%

{"folios":[{"folio":"","text":"Und ein pferit Sie mir mit meinen knechten oder fulpend
 Sen so was meinen kam weg
 deme Say mir machend
 und vriend Sie fuerst duf
 und vil in uns an dey and
 und Sie pferit vns an dey der petrel und was ze mot ein groffer
 nebel dz wir kum ire pferd
 und also mit groffer arbeit kenne
 wir ze mieten tag zu lant
 binstapel vff Say berg do
 do pfer ich die bucher So gar
 vil bawrey wogey in tone
 Sie in stier So bin gebey hand
 so find mines vatter v schrey
 wogey so in dem enien
","addition1":"3","addition2":"","addition3":""}]}

Scoring

Fuzzy score35.8%
CER ↓70.4%

Speed

Model time, all inputs150.3 s
Mean per input12.52 s
Slowest input22.37 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens98.9K
Output tokens2.6K
Total tokens101.5K
Input cost$0.0099
Output cost$0.0005
Total cost$0.0104

Priced from 2026-08-10 · Input $/M $0.10 · Output $/M $0.20

Result 86 of 177

Test T1486 at 2026-08-14

manuscript transcription handwritten 15 de prose

huggingface swiss-ai/apertus-v1.5-70b · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score90.0%
CER ↓10.4%

{"folios":[{"folio":"3","text":"Und ein pfert die mir vnd
minen bruderen vber guldend
San So was menen kunig weg
demne San wir machsend
vnd vriehend die fuerst vnd
vil in vng andezen vnd
vnd die pfert vns vng an die
petel vnd was ze mol ein groffer
nebel da wir kunig gesachend
vnd also mit groffer arbeit keme
wir ze mitten tag zu sant
Kunigoffel vff den berg do
So sich ir die bucher So gar
vil hauen wepen in stouze
Die in feur ze hin gebrachend
So stund mines vaters schgen
wagen off in dem einen
","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score69.1%
CER ↓35.8%

Speed

Model time, all inputs226.8 s
Mean per input18.90 s
Slowest input20.61 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens98.9K
Output tokens2.5K
Total tokens101.4K
Input cost$0.0811
Output cost$0.0073
Total cost$0.0884

Priced from 2026-08-10 · Input $/M $0.82 · Output $/M $2.92

Result 87 of 177

Test T1456 at 2026-08-04

manuscript transcription handwritten 15 de prose

x-ai grok-4.5 · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score96.8%
CER ↓2.4%

{"folios":[{"folio":"3","text":"Vnd ein pferit die mir vnd
minen knechten vber hulfend
den do was nienen kein weg
denne den wir machtend
vnd ziehend die knechte dick
vnd vil in vntz an den arb
vnd die pferit vntz an die
ketel vnd was ze mol ein grosser
nebel dz wir kum gesehend
vnd als mit grosser arbeit kame
wir ze mittem tag zuo sant
kristoffel vff den berg do
do sach ich die buocher do gar
vil herren wapen jn stont
die ir stir do hin geben hand
do stund mines vatters schiltgen
wapen och in dem einen","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score83.2%
CER ↓16.3%

Speed

Model time, all inputs540.9 s
Mean per input45.08 s
Slowest input100.78 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens40.1K
Output tokens2.8K
Total tokens42.9K
Input cost$0.0802
Output cost$0.0165
Total cost$0.2612
Reasoning cost usd$0.1644
Total reasoning tokens27.4K

Priced from 2026-08-04 · Input $/M $2.00 · Output $/M $6.00

Result 88 of 177

Test T1396 at 2026-07-25

manuscript transcription handwritten 15 de prose

openrouter moonshotai/kimi-k3 · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score95.4%
CER ↓4.3%

{"folios":[{"folio":"3","text":"vnd ein pferit die mir vnd
minen knechten wider luffend
sen do was nimen lang weg
denne den wir machtend
vnd viehend die knecht sich
vnd vil in vns an den arb
vnd die pferit vns an die
stel vnd was ze mol ein grosse
nebel dz wir kum gesahent
vnd also mit grosser arbeit kome
wir ze mittem tag zu sant
kristoffel vff den berg do
do sach ich die buecher so gar
vil gerren wopen in stou
die ir stur dd hin gesyen hand
do stund mines vatters pflagen
wopen och in dem einem","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score79.7%
CER ↓21.2%

Speed

Model time, all inputs6239.7 s
Mean per input519.97 s
Slowest input1729.60 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens53.7K
Output tokens204.8K
Total tokens258.5K
Input cost$0.1496
Output cost$3.07
Total cost$3.22

Priced from 2026-07-25 · Input $/M $3.00 · Output $/M $15.00

Result 89 of 177

Test T1441 at 2026-07-25

manuscript transcription handwritten 15 de prose

genai gemini-3.5-flash-lite · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score94.9%
CER ↓4.8%

{"folios":[{"folio":"3","text":"Vnd ein pferit die mir vnd
minen knechten vber Rulfend
Gen Do was menan kein weg
denne den wir machtend
vnd vihend die knechte dut
vnd vil in vns an den arb
vnd die pferit vns an die
settel vnd was ze mol ein grosser
nebel daz wir kum gesehend
vnd als mit grosser arbeit kame
wir ze mittem tag zu sant
christoffel off den berg do
do sach ich die bücher do gar
vil herren wopen in stoue
die ir für deltyn geben hand
do stünd mines vatters rügen
wopen ad in dem sinen","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score73.2%
CER ↓28.8%

Speed

Model time, all inputs391.3 s
Mean per input32.60 s
Slowest input55.87 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens19.1K
Output tokens2.8K
Total tokens22K
Input cost$0.0057
Output cost$0.0071
Total cost$0.0128

Priced from 2026-07-25 · Input $/M $0.30 · Output $/M $2.50

Result 90 of 177

Test T1381 at 2026-07-25

manuscript transcription handwritten 15 de prose

openai gpt-5.6-luna · temp 0.0 · dataclass Document

Response vs ground truth

One model response from this run. The per-input comparison needs JavaScript.

Fuzzy score87.3%
CER ↓14.0%

{"folios":[{"folio":"3","text":"vnd ein pferit Die mir mit
minen knechten wider hulfend
han So was menig lan weg
denne Do mir machernd
vnd vichtend Si knechte frib
vnd vil mir vnder an den arm
vnd Si pfiert vns an Si
Rtere vnd vns ze mol ein grosse
nebet dz wir kumy geschachend
vnd als mit grosser arbeite kame
wir zů mitten tag zu hant
kuntschaft vff Sin Berg So
So hueb ich die lücher Sogar
nit herren wogeny zu hane
Sie w für Edem g?äly hand
Do fründ mineb matterz klag
wogen ast in dem","addition1":"","addition2":"","addition3":""}]}

Scoring

Fuzzy score58.1%
CER ↓46.3%

Speed

Model time, all inputs232.7 s
Mean per input19.39 s
Slowest input30.60 s
Inputs timed12

Summed model time, not elapsed: requests run in parallel and the worker count is not recorded, so the run finished sooner than this.

Costs / Pricing

Input tokens44.4K
Output tokens24.2K
Total tokens68.6K
Input cost$0.0444
Output cost$0.1449
Total cost$0.1894

Priced from 2026-07-25 · Input $/M $1.00 · Output $/M $6.00