Long documents
Prompts that approach the documented context limit
Claude Opus 4.8
Claude Opus 4.8 has the larger documented context window.
Confidence: documented
Claude Opus 4.8 vs GPT-OSS 20B
Updated October 10, 2026. Rank says Claude Opus 4.8 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
Claude Opus 4.8 has the higher public score, 69.12 versus 33.51, and the 90% score intervals do not overlap. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 3
- Claude Opus 4.8 only
- 37
- GPT-OSS 20B only
- 4
- Like-for-like categories
- 1 / 8
Supported: Claude Opus 4.8 and GPT-OSS 20BHow the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
GPT-OSS 20B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-OSS 20B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GPT-OSS 20B does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GPT-OSS 20B has no comparable published API token rate.
Confidence: rate-fallbackRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
60.8Claude Opus 4.819.0GPT-OSS 20B
Directional only · BenchAlign v5.8
Claude Opus 4.8 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
37 Claude Opus 4.8 only
3 Shared
4 GPT-OSS 20B only
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
HLEKnowledge
Normalized gap 47.0Claude Opus 4.8:57.9%GPT-OSS 20B:10.9%SWE-bench VerifiedCoding
Normalized gap 27.9Claude Opus 4.8:88.6%GPT-OSS 20B:60.7%GPQAKnowledge
Normalized gap 22.1Claude Opus 4.8:93.6%GPT-OSS 20B:71.5%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Knowledge
Like-for-like- Claude Opus 4.8
- 70.7
- Supported · #14/177
- GPT-OSS 20B
- 33.9
- Supported · #134/177
- Basis
- BenchAlign v5.8 lane · 6 vs 3 public rows
- Reading
- Claude Opus 4.8 leads
Agentic
Directional only- Claude Opus 4.8
- 61.6
- Supported · #20/123
- GPT-OSS 20B
- 14.2
- Estimated · #111/123
- Basis
- BenchAlign v5.8 lane · 12 vs 0 public rows
- Reading
- Directional only
Coding
Directional only- Claude Opus 4.8
- 60.8
- Supported · #19/146
- GPT-OSS 20B
- 19.0
- Estimated · #119/146
- Basis
- BenchAlign v5.8 lane · 11 vs 2 public rows
- Reading
- Directional only
Instruction following
Directional only- Claude Opus 4.8
- 75.4
- #61/127
- GPT-OSS 20B
- 79.2
- #57/127
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Opus 4.8
- 62.9
- #24/28
- GPT-OSS 20B
- 49.8
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 91.2
- #5/54
- GPT-OSS 20B
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not ranked
- GPT-OSS 20B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.8
- 65.7
- #2/7
- GPT-OSS 20B
- Not ranked
- Basis
- Provisional lane · 3 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | GPT-OSS 20B | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 70.7Supported · #14/177 | 33.9Supported · #134/177 | Like-for-likeBenchAlign v5.8 lane · 6 vs 3 public rows | Claude Opus 4.8 leads |
| Agentic | 61.6Supported · #20/123 | 14.2Estimated · #111/123 | Directional onlyBenchAlign v5.8 lane · 12 vs 0 public rows | Directional only |
| Coding | 60.8Supported · #19/146 | 19.0Estimated · #119/146 | Directional onlyBenchAlign v5.8 lane · 11 vs 2 public rows | Directional only |
| Instruction following | 75.4#61/127 | 79.2#57/127 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Reasoning | 62.9#24/28 | 49.8Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multimodal | 91.2#5/54 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 65.7#2/7 | Not ranked | Not comparableProvisional lane · 3 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Claude Opus 4.8
- $0.0175
- Fits in one request
- GPT-OSS 20B
- Self-hosted; infrastructure cost varies
- Fits in one request
GPT-OSS 20B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.8
- $0.325
- Fits in one request
- GPT-OSS 20B
- Self-hosted; infrastructure cost varies
- Fits in one request
GPT-OSS 20B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Opus 4.8
- $1.35
- Fits in one request
- Cached input priced at the published list-input rate
- GPT-OSS 20B
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
GPT-OSS 20B does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GPT-OSS 20B has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.8GPT-OSS 20B
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
GPT-OSS 20B
128K
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewGPT-OSS 20B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.8
Not published
GPT-OSS 20B
No comparable hosted API rate
Documented inputs
Claude Opus 4.8
text, image
Anthropic model overviewGPT-OSS 20B
Not sourced
Documented outputs
Claude Opus 4.8
GPT-OSS 20B
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewGPT-OSS 20B
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
GPT-OSS 20B
Non-Reasoning
Weight access
Claude Opus 4.8
Proprietary
GPT-OSS 20B
Open Weight
License
Claude Opus 4.8
Proprietary
GPT-OSS 20B
Open Weight
Release date
Claude Opus 4.8
2026-05-28
GPT-OSS 20B
2025-08-05
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Claude Opus 4.8 has the higher public score, 69.12 versus 33.51, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Claude Opus 4.8 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Opus 4.8 or GPT-OSS 20B?
Claude Opus 4.8 has the higher public score, 69.12 versus 33.51, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Claude Opus 4.8 or GPT-OSS 20B?
Claude Opus 4.8 scores higher for coding on the public lane, 60.8 to 19. GPT-OSS 20B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude Opus 4.8 or GPT-OSS 20B?
Claude Opus 4.8 scores higher for agentic tasks on the public lane, 61.6 to 14.2. GPT-OSS 20B is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Opus 4.8 or GPT-OSS 20B?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Claude Opus 4.8 or GPT-OSS 20B?
Claude Opus 4.8 has the larger documented context window: 1M, compared with 128K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence44 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceGPT-OSS 20B—Not directly comparable
Terminal-Bench 2.1
Claude Opus 4.874.6%SourceGPT-OSS 20B—Not directly comparable
BrowseComp
Claude Opus 4.884.3%SourceGPT-OSS 20B—Not directly comparable
DeepSearchQA
Claude Opus 4.893.1%SourceGPT-OSS 20B—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceGPT-OSS 20B—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceGPT-OSS 20B—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceGPT-OSS 20B—Not directly comparable
Toolathlon
Claude Opus 4.859.9%SourceGPT-OSS 20B—Not directly comparable
Gert Labs
Claude Opus 4.872.97%SourceGPT-OSS 20B—Not directly comparable
ResearchClawBench
Claude Opus 4.821.1%SourceGPT-OSS 20B—Not directly comparable
OSWorld 2.0
Claude Opus 4.820.6%SourceGPT-OSS 20B—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.871.9%SourceGPT-OSS 20B—Not directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceGPT-OSS 20B60.7%SourceClaude Opus 4.8 leads this result
SWE-bench Pro
Claude Opus 4.869.2%SourceGPT-OSS 20B—Not directly comparable
SWE Multilingual
Claude Opus 4.884.4%SourceGPT-OSS 20B—Not directly comparable
SWE Multimodal
Claude Opus 4.838.4%SourceGPT-OSS 20B—Not directly comparable
Terminal-Bench 2.1
Claude Opus 4.874.6%SourceGPT-OSS 20B—Not directly comparable
cursorBench31
Claude Opus 4.858.4%SourceGPT-OSS 20B—Not directly comparable
CursorBench 3.2
Claude Opus 4.862.3%SourceGPT-OSS 20B—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceGPT-OSS 20B—Not directly comparable
LiveCodeBench (Vals)
Claude Opus 4.887.8%SourceGPT-OSS 20B—Not directly comparable
SWE-bench (Vals)
Claude Opus 4.888.6%SourceGPT-OSS 20B—Not directly comparable
PostTrainBench v1.1
Claude Opus 4.832.9%SourceGPT-OSS 20B—Not directly comparable
React Native Evals
Claude Opus 4.8—GPT-OSS 20B71%SourceNot directly comparable
Reasoning
Multimodal
Knowledge
GPQA
Claude Opus 4.893.6%SourceGPT-OSS 20B71.5%SourceClaude Opus 4.8 leads this result
GPQA-D
Claude Opus 4.893.6%SourceGPT-OSS 20B—Not directly comparable
HLE
Claude Opus 4.857.9%SourceGPT-OSS 20B10.9%SourceClaude Opus 4.8 leads this result
HLE w/o tools
Claude Opus 4.849.8%SourceGPT-OSS 20B—Not directly comparable
GPQA Diamond (Vals)
Claude Opus 4.892.4%SourceGPT-OSS 20B—Not directly comparable
MMLU-Pro (Vals)
Claude Opus 4.889.6%SourceGPT-OSS 20B—Not directly comparable
MMLU
Claude Opus 4.8—GPT-OSS 20B85.3%SourceNot directly comparable
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceGPT-OSS 20B—Not directly comparable
Math
USAMO 2026
Claude Opus 4.896.7%SourceGPT-OSS 20B—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Opus 4.847.241%SourceGPT-OSS 20B—Not directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.831.250%SourceGPT-OSS 20B—Not directly comparable
AIME 2024
Claude Opus 4.8—GPT-OSS 20B92.1%SourceNot directly comparable
AIME 2025
Claude Opus 4.8—GPT-OSS 20B91.7%SourceNot directly comparable
44 public results · 3 shared
Watch Claude Opus 4.8 vs GPT-OSS 20B
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 5,500+ readers.
Last updated October 10, 2026