Coding
Directional only- Claude Opus 4.8
- 81.1
- GPT-4.1 mini
- 23.6
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Claude Opus 4.8 vs GPT-4.1 mini
Updated August 26, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Opus 4.8 has the higher public score, 76.45 versus 44.24, and the 90% score intervals do not overlap.
3 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Chat turn cost
1K fresh input + 500 output tokens
GPT-4.1 mini
GPT-4.1 mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
GPT-4.1 mini
GPT-4.1 mini has the lower estimated token cost for this stated workload. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
GPT-4.1 mini
GPT-4.1 mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
30 Claude Opus 4.8 only
3 Shared
2 GPT-4.1 mini only
- Shared results
- 3
- Claude Opus 4.8 only
- 30
- GPT-4.1 mini only
- 2
- Like-for-like categories
- 0 / 8
3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Knowledge
Directional only- Claude Opus 4.8
- 62.7
- GPT-4.1 mini
- 64.2
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Math
Directional only- Claude Opus 4.8
- 53.9
- GPT-4.1 mini
- 4.5
- Weighted basis
- 3 vs 1 rows
- Reading
- Directional only
Agentic
Not comparable- Claude Opus 4.8
- 80.3
- GPT-4.1 mini
- Not measured
- Weighted basis
- 3 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 4.8
- 72.1
- GPT-4.1 mini
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not measured
- GPT-4.1 mini
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 77.0
- GPT-4.1 mini
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.8
- Not measured
- GPT-4.1 mini
- 88.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | GPT-4.1 mini | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 81.1 | 23.6 | Directional only2 vs 1 rows | Directional only |
| Knowledge | 62.7 | 64.2 | Directional only2 vs 1 rows | Directional only |
| Math | 53.9 | 4.5 | Directional only3 vs 1 rows | Directional only |
| Agentic | 80.3 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Reasoning | 72.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 77.0 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Instruction following | Not measured | 88.5 | Not comparable0 vs 1 rows | Not comparable |
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.
SWE-bench Verified
Coding
Claude Opus 4.8: 88.6%GPT-4.1 mini: 23.6%Normalized gap 65.0Claude Opus 4.8 source GPT-4.1 mini sourceFrontierMath v2 (Tiers 1-3)
Math
GPQA
Knowledge
Claude Opus 4.8: 93.6%GPT-4.1 mini: 64.2%Normalized gap 29.4Claude Opus 4.8 source GPT-4.1 mini source
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-4.1 mini
- $0.0012
- Fits in one request
GPT-4.1 mini has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.8
- $0.325
- Fits in one request
- GPT-4.1 mini
- $0.0248
- Fits in one request
GPT-4.1 mini has the lower modeled cost
Costs use the listed standard API rates.
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-4.1 mini
- $0.104
- Fits in one request
- Cached input priced at the published list-input rate
GPT-4.1 mini has the lower modeled cost
Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate.
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-4.1 mini
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
GPT-4.1 mini
1M
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewGPT-4.1 mini
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-4.1 mini
Not published
Documented inputs
Claude Opus 4.8
text, image
Anthropic model overviewGPT-4.1 mini
Not sourced
Documented outputs
Claude Opus 4.8
GPT-4.1 mini
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewGPT-4.1 mini
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
GPT-4.1 mini
Non-Reasoning
Weight access
Claude Opus 4.8
Proprietary
GPT-4.1 mini
Proprietary
License
Claude Opus 4.8
Proprietary
GPT-4.1 mini
Proprietary
Release date
Claude Opus 4.8
2026-05-28
GPT-4.1 mini
2025-04-14
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, 76.45 versus 44.24, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.325 vs $0.0248. Cache-heavy agent loop: $1.35 vs $0.104.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence35 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceGPT-4.1 mini—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceGPT-4.1 mini—Not directly comparable
BrowseComp
Claude Opus 4.884.3%SourceGPT-4.1 mini—Not directly comparable
DeepSearchQA
Claude Opus 4.893.1%SourceGPT-4.1 mini—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceGPT-4.1 mini—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceGPT-4.1 mini—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceGPT-4.1 mini—Not directly comparable
Toolathlon
Claude Opus 4.859.9%SourceGPT-4.1 mini—Not directly comparable
Gert Labs
Claude Opus 4.872.97%SourceGPT-4.1 mini—Not directly comparable
ResearchClawBench
Claude Opus 4.821.1%SourceGPT-4.1 mini—Not directly comparable
OSWorld 2.0
Claude Opus 4.820.6%SourceGPT-4.1 mini—Not directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceGPT-4.1 mini23.6%SourceClaude Opus 4.8 leads this result
SWE-bench Pro
Claude Opus 4.869.2%SourceGPT-4.1 mini—Not directly comparable
SWE Multilingual
Claude Opus 4.884.4%SourceGPT-4.1 mini—Not directly comparable
SWE Multimodal
Claude Opus 4.838.4%SourceGPT-4.1 mini—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceGPT-4.1 mini—Not directly comparable
cursorBench31
Claude Opus 4.858.4%SourceGPT-4.1 mini—Not directly comparable
cursorBench32
Claude Opus 4.862.3%SourceGPT-4.1 mini—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceGPT-4.1 mini—Not directly comparable
Reasoning
Knowledge
GPQA
Claude Opus 4.893.6%SourceGPT-4.1 mini64.2%SourceClaude Opus 4.8 leads this result
GPQA-D
Claude Opus 4.893.6%SourceGPT-4.1 mini—Not directly comparable
HLE
Claude Opus 4.857.9%SourceGPT-4.1 mini—Not directly comparable
HLE w/o tools
Claude Opus 4.849.8%SourceGPT-4.1 mini—Not directly comparable
MMLU
Claude Opus 4.8—GPT-4.1 mini87.5%SourceNot directly comparable
Math
USAMO 2026
Claude Opus 4.896.7%SourceGPT-4.1 mini—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Opus 4.847.241%GPT-4.1 mini4.483%Claude Opus 4.8 leads this result
FrontierMath v2 (Tier 4)
Claude Opus 4.831.250%SourceGPT-4.1 mini—Not directly comparable
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceGPT-4.1 mini—Not directly comparable
Multimodal
OfficeQA Pro
Claude Opus 4.866.2%SourceGPT-4.1 mini—Not directly comparable
ScreenSpot Pro
Claude Opus 4.887.9%SourceGPT-4.1 mini—Not directly comparable
CharXiv
Claude Opus 4.889.9%SourceGPT-4.1 mini—Not directly comparable
CharXiv w/o tools
Claude Opus 4.880.5%SourceGPT-4.1 mini—Not directly comparable
Instruction following
IFEval
Claude Opus 4.8—GPT-4.1 mini88.5%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Opus 4.8 or GPT-4.1 mini?
Claude Opus 4.8 has the higher public score, 76.45 versus 44.24, 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-4.1 mini?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. 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-4.1 mini?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Claude Opus 4.8 or GPT-4.1 mini?
For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.0012 on GPT-4.1 mini; repository review costs $0.325 and $0.0248; the cache-heavy agent loop costs $1.35 and $0.104. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.8 or GPT-4.1 mini?
Both models list the same context window, 1M.
Related comparisons
Last updated August 26, 2026
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