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Claude Fable 5 vs gpt-oss-20b

Claude Fable 5 leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 49.6 to 10.0, and gpt-oss-20b costs 333.3x less per output token ($0.15 vs $50.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.

Claude Fable 5Anthropic
Coding
79.3
Overall
79.0
Output $/M
$50.00
50
gpt-oss-20bOpenAI
Coding
No data
Overall
38.5
Output $/M
$0.15
1
vs boards won of 51 shared

Claude Fable 5 or gpt-oss-20b: which to pick

Only Claude Fable 5 has a coding score, 79.3 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding.

Pick gpt-oss-20b for output tokens 333.3x cheaper ($0.15 vs $50.00 per million) and work measured by IFBench, where it leads.

Shared results
51
Claude Fable 5 only
76
gpt-oss-20b only
11
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Claude Fable 5 79.3 from 6 benchmarks, gpt-oss-20b not benchmarked.
Widest category
Web design, 50.9 points apart on average over 2 shared benchmarks.
Widest single gap
Design Arena: websites: Claude Fable 5 1295 against gpt-oss-20b 852, 55.4 points apart on a 0 to 100 scale.
Output price
Claude Fable 5 $50.00 against gpt-oss-20b $0.15 per million output tokens, 333.3x apart.
Context window
Claude Fable 5 takes 1M tokens, gpt-oss-20b 131K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryClaude Fable 5Barsgpt-oss-20bTies
Coding70
Intelligence20
Agentic work10
Reasoning80
Math30
Knowledge80
Web design20
General191
All shared boards501
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
LiveBench coding98.3%Not measuredOnly Claude Fable 5 measured
LMArena WebDev1624Not measuredOnly Claude Fable 5 measured
AA Coding Index76.5Not measuredOnly Claude Fable 5 measured
LiveCodeBench (Vals AI)89.8%80.4%Claude Fable 5
SWE-bench Verified (Vals AI)95.0%Not measuredOnly Claude Fable 5 measured
Terminal-Bench 4 (Vals AI)41.4%Not measuredOnly Claude Fable 5 measured
Vibe Code Bench (Vals AI)90.3%Not measuredOnly Claude Fable 5 measured
Code migration (Vals AI)55.1%Not measuredOnly Claude Fable 5 measured
ProgramBench (Vals AI)2.0%Not measuredOnly Claude Fable 5 measured
Terminal-Bench 2.1 (Vals AI)80.5%Not measuredOnly Claude Fable 5 measured
LiveCodeBench (Artificial Analysis run)Not measured77.7%Only gpt-oss-20b measured
SciCode61.0%38.9%Claude Fable 5
Terminal-Bench Hard (Artificial Analysis run)62.9%10.6%Claude Fable 5
Terminal-BenchNot measured3.4%Only gpt-oss-20b measured
FrontierCode53.5%Not measuredOnly Claude Fable 5 measured
FrontierSWE47.0%Not measuredOnly Claude Fable 5 measured
GSO-Bench78.4%Not measuredOnly Claude Fable 5 measured
WeirdML91.9%40.9%Claude Fable 5
MirrorCode63.9%Not measuredOnly Claude Fable 5 measured
ALE-Bench2041.3566.0Claude Fable 5
LMArena Text: coding15181307Claude Fable 5
LMArena Text: software and IT15131311Claude Fable 5
LMArena WebDev: React1631Not measuredOnly Claude Fable 5 measured
LMArena WebDev: HTML1651Not measuredOnly Claude Fable 5 measured
LMArena WebDev: from an image1623Not measuredOnly Claude Fable 5 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
AA Intelligence Index49.610.0Claude Fable 5
Epoch Capabilities Index163.4137.7Claude Fable 5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
AA Agentic Index50.7Not measuredOnly Claude Fable 5 measured
Design Arena: agents building web apps1261Not measuredOnly Claude Fable 5 measured
Design Arena: agents building full-stack apps1280Not measuredOnly Claude Fable 5 measured
Design Arena: agents building mobile apps1264Not measuredOnly Claude Fable 5 measured
Design Arena: agents building Android apps1284Not measuredOnly Claude Fable 5 measured
Design Arena: agents building Godot games1292Not measuredOnly Claude Fable 5 measured
Design Arena: agents building games1285Not measuredOnly Claude Fable 5 measured
Design Arena: HTML slides1227Not measuredOnly Claude Fable 5 measured
Design Arena: PowerPoint slides1270Not measuredOnly Claude Fable 5 measured
LiveBench research86.9%Not measuredOnly Claude Fable 5 measured
LiveBench browser92.0%Not measuredOnly Claude Fable 5 measured
LiveBench long agentic53.2%Not measuredOnly Claude Fable 5 measured
Finance Agent (Vals AI)56.3%Not measuredOnly Claude Fable 5 measured
Tax Agent Bench (Vals AI)38.3%Not measuredOnly Claude Fable 5 measured
Legal Research Bench (Vals AI)49.5%Not measuredOnly Claude Fable 5 measured
Excel Modeling Benchmark (Vals AI)73.7%Not measuredOnly Claude Fable 5 measured
Terminal-Bench-Science (Vals AI)15.7%Not measuredOnly Claude Fable 5 measured
τ²-Bench Telecom98.5%60.2%Claude Fable 5
APEX-Agents63.6%Not measuredOnly Claude Fable 5 measured
Remote Labor Index16.1%Not measuredOnly Claude Fable 5 measured
PostTrainBench41.8%Not measuredOnly Claude Fable 5 measured
Vending-Bench 2$5,680Not measuredOnly Claude Fable 5 measured
LMArena Search1229Not measuredOnly Claude Fable 5 measured
BrowseComp-PlusNot measured50.6%Only gpt-oss-20b measured
Neither model has a result on the other 17 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
GPQA Diamond93.2%68.9%Claude Fable 5
LiveBench reasoning89.7%Not measuredOnly Claude Fable 5 measured
MMMU Pro (Vals AI)89.3%Not measuredOnly Claude Fable 5 measured
GPQA Diamond (Artificial Analysis run)92.6%68.8%Claude Fable 5
Humanity's Last Exam (Artificial Analysis run)55.5%11.0%Claude Fable 5
GPQA Diamond (Epoch AI run)85.9%60.8%Claude Fable 5
ARC-AGI98.5%Not measuredOnly Claude Fable 5 measured
ARC-AGI-289.2%Not measuredOnly Claude Fable 5 measured
SimpleBench81.9%Not measuredOnly Claude Fable 5 measured
Chess puzzles47.0%Not measuredOnly Claude Fable 5 measured
Mystery game puzzles52.0%Not measuredOnly Claude Fable 5 measured
EBR-bench39.5%Not measuredOnly Claude Fable 5 measured
LMArena Text: hard prompts15071274Claude Fable 5
LMArena Text: expert15341258Claude Fable 5
LMArena Text: hard prompts in English15091292Claude Fable 5
LMArena Vision: diagrams1357Not measuredOnly Claude Fable 5 measured
LMArena Vision: homework1361Not measuredOnly Claude Fable 5 measured
Kagi LLM Benchmark91.4%53.2%Claude Fable 5
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
AIMENot measured86.0%Only gpt-oss-20b measured
MATH 500 (Vals AI)Not measured94.2%Only gpt-oss-20b measured
MGSM (Vals AI)Not measured89.0%Only gpt-oss-20b measured
AA Math IndexNot measured89.3Only gpt-oss-20b measured
AIME 2025 (Artificial Analysis run)Not measured89.3%Only gpt-oss-20b measured
OTIS Mock AIME100.0%65.3%Claude Fable 5
FrontierMath, tiers 1 to 387.0%Not measuredOnly Claude Fable 5 measured
FrontierMath, tier 490.2%Not measuredOnly Claude Fable 5 measured
ProofBench95.0%Not measuredOnly Claude Fable 5 measured
LMArena Text: math15161317Claude Fable 5
LMArena Text: mathematical work15151305Claude Fable 5
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
Knowledge benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
MMLU Pro91.5%71.6%Claude Fable 5
LegalBench (Vals AI)88.6%70.8%Claude Fable 5
CaseLaw (Vals AI)Not measured43.8%Only gpt-oss-20b measured
CorpFin (Vals AI)71.8%53.1%Claude Fable 5
TaxEval (Vals AI)76.9%63.7%Claude Fable 5
MortgageTax (Vals AI)68.9%Not measuredOnly Claude Fable 5 measured
MedQA (Vals AI)Not measured82.9%Only gpt-oss-20b measured
MedCode (Vals AI)56.1%Not measuredOnly Claude Fable 5 measured
MMLU Pro (Artificial Analysis run)Not measured74.8%Only gpt-oss-20b measured
SimpleQA Verified70.7%Not measuredOnly Claude Fable 5 measured
LMArena Text: science15061296Claude Fable 5
LMArena Text: medicine and healthcare14801310Claude Fable 5
LMArena Text: legal and government14981280Claude Fable 5
LMArena Text: business and finance14801284Claude Fable 5
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index20
Web design benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
Design Arena: websites1295852Claude Fable 5
Design Arena: UI components1316Not measuredOnly Claude Fable 5 measured
Design Arena: game dev1335Not measuredOnly Claude Fable 5 measured
Design Arena: data viz1304933Claude Fable 5
Design Arena: 3D1318Not measuredOnly Claude Fable 5 measured
Design Arena: all code categories1310Not measuredOnly Claude Fable 5 measured
Design Arena: SVG1302Not measuredOnly Claude Fable 5 measured
Design Arena: ASCII art1329Not measuredOnly Claude Fable 5 measured
LiveBench design84.7%Not measuredOnly Claude Fable 5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index191
General benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
LiveBench data analysis80.5%Not measuredOnly Claude Fable 5 measured
Public Benefits Bench (Vals AI)70.4%Not measuredOnly Claude Fable 5 measured
SAGE (Vals AI)51.9%Not measuredOnly Claude Fable 5 measured
MedScribe (Vals AI)88.5%Not measuredOnly Claude Fable 5 measured
Vals Multimodal Index74.2%Not measuredOnly Claude Fable 5 measured
IFBench63.5%65.1%gpt-oss-20b
Long context reasoning (AA-LCR)82.3%34.7%Claude Fable 5
DTBench98.4%68.0%Claude Fable 5
LMCA61.2%14.5%Claude Fable 5
Surface Evolver Bench95.0%Not measuredOnly Claude Fable 5 measured
Furniture assembly35.8%Not measuredOnly Claude Fable 5 measured
LMArena Text14911288Claude Fable 5
LMArena Text: instruction following15021236Claude Fable 5
LMArena Text: creative writing14941201Claude Fable 5
LMArena Vision1325Not measuredOnly Claude Fable 5 measured
LMArena Text: English14981303Claude Fable 5
LMArena Text: non-English14821269Claude Fable 5
LMArena Text: Chinese15431315Claude Fable 5
LMArena Text: German14861255Claude Fable 5
LMArena Text: Japanese15041244Claude Fable 5
LMArena Text: Korean14871236Claude Fable 5
LMArena Text: French1505Not measuredOnly Claude Fable 5 measured
LMArena Text: Spanish14981267Claude Fable 5
LMArena Text: Russian15031278Claude Fable 5
LMArena Text: Polish14941252Claude Fable 5
LMArena Text: multi-turn15041268Claude Fable 5
LMArena Text: longer queries15101250Claude Fable 5
LMArena Text: writing and language15011238Claude Fable 5
LMArena Text: entertainment and media14821216Claude Fable 5
LMArena Vision: English1323Not measuredOnly Claude Fable 5 measured
LMArena Vision: Chinese1373Not measuredOnly Claude Fable 5 measured
LMArena Vision: reading text1337Not measuredOnly Claude Fable 5 measured
LMArena Vision: humor1341Not measuredOnly Claude Fable 5 measured
LMArena Vision: creative writing1338Not measuredOnly Claude Fable 5 measured
LMArena Document1496Not measuredOnly Claude Fable 5 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Fable 5 and gpt-oss-20b
BenchmarkClaude Fable 5gpt-oss-20bLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Claude Fable 5$0.035Fits in one request
gpt-oss-20b$0.0001Fits in one request

gpt-oss-20b costs less

Repository review

50K input + 3K output tokens

Claude Fable 5$0.650Fits in one request
gpt-oss-20b$0.0019Fits in one request

gpt-oss-20b costs less

Agent loop

200K input + 10K output tokens

Claude Fable 5$2.50Fits in one request
gpt-oss-20b$0.0075Exceeds the context window

gpt-oss-20b costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Claude Fable 5 and gpt-oss-20b
SpecificationAnthropic Claude Fable 5OpenAI gpt-oss-20b
MakerAnthropicOpenAI
WeightsNo public weights listedOpen weights
ReleasedJune 9, 2026August 5, 2025
Context window1M131K
Input $/Mtok$10.00$0.03
Output $/Mtok$50.00$0.15
Coding index79.3Not benchmarked
Independent measurements behind it60
Cost per solved task$2.16Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Fable 5 better than gpt-oss-20b for coding?

Only Claude Fable 5 has a coding score, 79.3 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding. Pick gpt-oss-20b for output tokens 333.3x cheaper ($0.15 vs $50.00 per million) and work measured by IFBench, where it leads.

Which is cheaper, Claude Fable 5 or gpt-oss-20b?

Claude Fable 5 costs $10.00 per million input tokens and $50.00 per million output tokens; gpt-oss-20b costs $0.03 and $0.15. Cost per solved task is known for Claude Fable 5 only.

Which has the bigger context window, Claude Fable 5 or gpt-oss-20b?

Claude Fable 5, with 1M tokens against 131K.

How many benchmarks is the Claude Fable 5 vs gpt-oss-20b comparison based on?

51 benchmarks have a result for both models as of October 22, 2026. Claude Fable 5's coding index rests on 6 independent benchmarks and gpt-oss-20b's on 0. Where only one model has a result, the page says so instead of naming a winner.

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