Agentic
Not comparable- Claude Opus 4.8
- 62.5
- Supported · #14/152
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- BenchAlign lane · 12 vs 4 public rows
- Reading
- Not comparable
Claude Opus 4.8 vs LongCat-Flash-Lite-Sparse
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
LongCat-Flash-Lite-Sparse is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
LongCat-Flash-Lite-Sparse is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat 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-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: rate-fallback
Repository 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
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
8 Shared
9 LongCat-Flash-Lite-Sparse only
- Shared results
- 8
- Claude Opus 4.8 only
- 30
- LongCat-Flash-Lite-Sparse only
- 9
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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.
Coding
Not comparable- Claude Opus 4.8
- 66.4
- Supported · #12/151
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- BenchAlign lane · 10 vs 4 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 4.8
- 55.5
- #18/20
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 4.8
- 71.4
- Supported · #9/183
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- BenchAlign lane · 6 vs 5 public rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.8
- 65.4
- #2/7
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- Provisional lane · 3 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not ranked
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 87.8
- #3/48
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.8
- 75.4
- #61/123
- LongCat-Flash-Lite-Sparse
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | LongCat-Flash-Lite-Sparse | Basis | Reading |
|---|---|---|---|---|
| Agentic | 62.5Supported · #14/152 | Not ranked | Not comparableBenchAlign lane · 12 vs 4 public rows | Not comparable |
| Coding | 66.4Supported · #12/151 | Not ranked | Not comparableBenchAlign lane · 10 vs 4 public rows | Not comparable |
| Reasoning | 55.5#18/20 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Knowledge | 71.4Supported · #9/183 | Not ranked | Not comparableBenchAlign lane · 6 vs 5 public rows | Not comparable |
| Math | 65.4#2/7 | Not ranked | Not comparableProvisional lane · 3 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 87.8#3/48 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Instruction following | 75.4#61/123 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
Terminal-Bench 2.0
Agentic
Claude Opus 4.8: 74.6%LongCat-Flash-Lite-Sparse: 33.7%Normalized gap 40.9Claude Opus 4.8 source LongCat-Flash-Lite-Sparse sourceBrowseComp
Agentic
Claude Opus 4.8: 84.3%LongCat-Flash-Lite-Sparse: 48.6%Normalized gap 35.7Claude Opus 4.8 source LongCat-Flash-Lite-Sparse sourceSWE-bench Pro
Coding
Claude Opus 4.8: 69.2%LongCat-Flash-Lite-Sparse: 40.6%Normalized gap 28.6Claude Opus 4.8 source LongCat-Flash-Lite-Sparse sourceSWE Multilingual
Coding
Claude Opus 4.8: 84.4%LongCat-Flash-Lite-Sparse: 59.3%Normalized gap 25.1Claude Opus 4.8 source LongCat-Flash-Lite-Sparse sourceSWE-bench Verified
Coding
Claude Opus 4.8: 88.6%LongCat-Flash-Lite-Sparse: 68.2%Normalized gap 20.4Claude Opus 4.8 source LongCat-Flash-Lite-Sparse 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
- LongCat-Flash-Lite-Sparse
- Self-hosted; infrastructure cost varies
- Fits in one request
LongCat-Flash-Lite-Sparse 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
- LongCat-Flash-Lite-Sparse
- Self-hosted; infrastructure cost varies
- Fits in one request
LongCat-Flash-Lite-Sparse 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
- LongCat-Flash-Lite-Sparse
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. LongCat-Flash-Lite-Sparse has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.8LongCat-Flash-Lite-Sparse
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
LongCat-Flash-Lite-Sparse
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewLongCat-Flash-Lite-Sparse
meituan-longcat/LongCat-Flash-Lite-Sparse
Meituan LongCat-Flash-Lite-Sparse model cardCached-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
LongCat-Flash-Lite-Sparse
No comparable hosted API rate
Meituan LongCat-Flash-Lite-Sparse model cardDocumented inputs
Claude Opus 4.8
text, image
Anthropic model overviewLongCat-Flash-Lite-Sparse
Not sourced
Documented outputs
Claude Opus 4.8
LongCat-Flash-Lite-Sparse
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewLongCat-Flash-Lite-Sparse
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
LongCat-Flash-Lite-Sparse
Reasoning
Weight access
Claude Opus 4.8
Proprietary
LongCat-Flash-Lite-Sparse
Open Weight
License
Claude Opus 4.8
Proprietary
LongCat-Flash-Lite-Sparse
Open Weight
Release date
Claude Opus 4.8
2026-05-28
LongCat-Flash-Lite-Sparse
2026-07-31
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- 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 evidence47 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceLongCat-Flash-Lite-Sparse33.7%SourceClaude Opus 4.8 leads this result
BrowseComp
Claude Opus 4.884.3%SourceLongCat-Flash-Lite-Sparse48.6%SourceClaude Opus 4.8 leads this result
DeepSearchQA
Claude Opus 4.893.1%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceLongCat-Flash-Lite-Sparse45.6%SourceClaude Opus 4.8 leads this result
Toolathlon
Claude Opus 4.859.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Gert Labs
Claude Opus 4.872.97%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
ResearchClawBench
Claude Opus 4.821.1%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
OSWorld 2.0
Claude Opus 4.820.6%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.871.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
VITA-Bench
Claude Opus 4.8—LongCat-Flash-Lite-Sparse21.7%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceLongCat-Flash-Lite-Sparse68.2%SourceClaude Opus 4.8 leads this result
SWE-bench Pro
Claude Opus 4.869.2%SourceLongCat-Flash-Lite-Sparse40.6%SourceClaude Opus 4.8 leads this result
SWE Multilingual
Claude Opus 4.884.4%SourceLongCat-Flash-Lite-Sparse59.3%SourceClaude Opus 4.8 leads this result
SWE Multimodal
Claude Opus 4.838.4%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceLongCat-Flash-Lite-Sparse33.7%SourceClaude Opus 4.8 leads this result
cursorBench31
Claude Opus 4.858.4%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
cursorBench32
Claude Opus 4.862.3%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
LiveCodeBench (Vals)
Claude Opus 4.887.8%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
SWE-bench (Vals)
Claude Opus 4.888.6%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Reasoning
Knowledge
GPQA
Claude Opus 4.893.6%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
GPQA-D
Claude Opus 4.893.6%SourceLongCat-Flash-Lite-Sparse69.5%SourceClaude Opus 4.8 leads this result
HLE
Claude Opus 4.857.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
HLE w/o tools
Claude Opus 4.849.8%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
GPQA Diamond (Vals)
Claude Opus 4.892.4%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
MMLU-Pro (Vals)
Claude Opus 4.889.6%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
MMLU
Claude Opus 4.8—LongCat-Flash-Lite-Sparse85.3%SourceNot directly comparable
MMLU-Pro
Claude Opus 4.8—LongCat-Flash-Lite-Sparse79.2%SourceNot directly comparable
CMMLU
Claude Opus 4.8—LongCat-Flash-Lite-Sparse84.3%SourceNot directly comparable
C-Eval
Claude Opus 4.8—LongCat-Flash-Lite-Sparse85.8%SourceNot directly comparable
Math
USAMO 2026
Claude Opus 4.896.7%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Opus 4.847.241%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.831.250%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
MATH-500
Claude Opus 4.8—LongCat-Flash-Lite-Sparse95.8%SourceNot directly comparable
AIME26
Claude Opus 4.8—LongCat-Flash-Lite-Sparse65.7%SourceNot directly comparable
HMMT Feb 2026
Claude Opus 4.8—LongCat-Flash-Lite-Sparse40.5%SourceNot directly comparable
IMOAnswerBench
Claude Opus 4.8—LongCat-Flash-Lite-Sparse49.4%SourceNot directly comparable
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Multimodal
OfficeQA Pro
Claude Opus 4.866.2%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
ScreenSpot Pro
Claude Opus 4.887.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
CharXiv
Claude Opus 4.889.9%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
CharXiv w/o tools
Claude Opus 4.880.5%SourceLongCat-Flash-Lite-Sparse—Not directly comparable
Frequently asked questions
Which is better, Claude Opus 4.8 or LongCat-Flash-Lite-Sparse?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Opus 4.8 or LongCat-Flash-Lite-Sparse?
LongCat-Flash-Lite-Sparse is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Opus 4.8 or LongCat-Flash-Lite-Sparse?
LongCat-Flash-Lite-Sparse is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Opus 4.8 or LongCat-Flash-Lite-Sparse?
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 LongCat-Flash-Lite-Sparse?
Both models list the same context window, 1M.
Related comparisons
Last updated September 10, 2026
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