Long documents
Prompts that approach the documented context limit
Ling 3.0 Flash Fin
Ling 3.0 Flash Fin has the larger documented context window.
Confidence: documented
Kimi K2.5 vs Ling 3.0 Flash Fin
Updated October 13, 2026. We do not rank this pair: at least one has no public score. 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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 0
- Kimi K2.5 only
- 68
- Ling 3.0 Flash Fin only
- 3
- Like-for-like categories
- 0 / 8
Supported: Kimi K2.5How 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
Ling 3.0 Flash Fin is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ling 3.0 Flash Fin is not ranked on the public lane for agentic, so no winner is named for agentic.
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
A complete comparable API-rate estimate is not available for both models.
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.
39.0Kimi K2.5—Ling 3.0 Flash Fin
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
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.
68 Kimi K2.5 only
3 Ling 3.0 Flash Fin only
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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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.
Agentic
Not comparable- Kimi K2.5
- 40.2
- Estimated · #61/123
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- BenchAlign v5.8 lane · 16 vs 3 public rows
- Reading
- Not comparable
Coding
Not comparable- Kimi K2.5
- 39.0
- Estimated · #66/148
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- BenchAlign v5.8 lane · 10 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Kimi K2.5
- 72.2
- Unranked · 3 rankable rows
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Kimi K2.5
- 70.4
- #32/54
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Kimi K2.5
- 51.3
- Estimated · #72/180
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- BenchAlign v5.8 lane · 8 vs 0 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Kimi K2.5
- 87.3
- #8/17
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Kimi K2.5
- 85.8
- #46/127
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Kimi K2.5
- 83.3
- Unranked · 7 rankable rows
- Ling 3.0 Flash Fin
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | Kimi K2.5 | Ling 3.0 Flash Fin | Basis | Reading |
|---|---|---|---|---|
| Agentic | 40.2Estimated · #61/123 | Not ranked | Not comparableBenchAlign v5.8 lane · 16 vs 3 public rows | Not comparable |
| Coding | 39.0Estimated · #66/148 | Not ranked | Not comparableBenchAlign v5.8 lane · 10 vs 0 public rows | Not comparable |
| Reasoning | 72.2Unranked · 3 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Multimodal | 70.4#32/54 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Knowledge | 51.3Estimated · #72/180 | Not ranked | Not comparableBenchAlign v5.8 lane · 8 vs 0 public rows | Not comparable |
| Multilingual | 87.3#8/17 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | 85.8#46/127 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 83.3Unranked · 7 rankable rows | Not ranked | Not comparableProvisional lane · 2 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.
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
- Kimi K2.5
- $0.0021
- Fits in one request
- Ling 3.0 Flash Fin
- API rate not published
- Fits in one request
Ling 3.0 Flash Fin has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Kimi K2.5
- $0.039
- Fits in one request
- Ling 3.0 Flash Fin
- API rate not published
- Fits in one request
Ling 3.0 Flash Fin has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Kimi K2.5
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
- Ling 3.0 Flash Fin
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate. Ling 3.0 Flash Fin 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.
SpecificationKimi K2.5Ling 3.0 Flash Fin
Context window
Maximum documented context; output-token limits may be lower.
Kimi K2.5
256K
Ling 3.0 Flash Fin
API model ID
Kimi K2.5
Not sourced
Ling 3.0 Flash Fin
inclusionai/ling-3.0-flash-fin
Vercel AI Gateway availabilityCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Kimi K2.5
Not published
Ling 3.0 Flash Fin
No comparable hosted API rate
Vercel AI Gateway availabilityDocumented inputs
Kimi K2.5
Not sourced
Ling 3.0 Flash Fin
Not sourced
Documented outputs
Kimi K2.5
Not sourced
Ling 3.0 Flash Fin
Not sourced
Provider availability
Kimi K2.5
Not sourced
Ling 3.0 Flash Fin
Not sourced
Reasoning profile
Kimi K2.5
Non-Reasoning
Ling 3.0 Flash Fin
Reasoning
Weight access
Kimi K2.5
Open Weight
Ling 3.0 Flash Fin
Proprietary
License
Kimi K2.5
Open Weight
Ling 3.0 Flash Fin
Proprietary
Release date
Kimi K2.5
2026-02-01
Ling 3.0 Flash Fin
2026-08-28
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Ling 3.0 Flash Fin has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Kimi K2.5 or Ling 3.0 Flash Fin?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Kimi K2.5 or Ling 3.0 Flash Fin?
Ling 3.0 Flash Fin is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Kimi K2.5 or Ling 3.0 Flash Fin?
Ling 3.0 Flash Fin is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Kimi K2.5 or Ling 3.0 Flash Fin?
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, Kimi K2.5 or Ling 3.0 Flash Fin?
Ling 3.0 Flash Fin has the larger documented context window: 262K, compared with 256K.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
Ling 3.0 Flash Fin
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence71 rows
Agentic
Terminal-Bench 2.0
Kimi K2.550.8%SourceLing 3.0 Flash Fin—Not directly comparable
BrowseComp
Kimi K2.560.6%SourceLing 3.0 Flash Fin—Not directly comparable
OSWorld-Verified
Kimi K2.563.3%SourceLing 3.0 Flash Fin—Not directly comparable
Claw-Eval
Kimi K2.552.3%SourceLing 3.0 Flash Fin—Not directly comparable
QwenClawBench
Kimi K2.554.3%SourceLing 3.0 Flash Fin—Not directly comparable
τ³-bench results
Kimi K2.565.7%SourceLing 3.0 Flash Fin—Not directly comparable
DeepSearchQA
Kimi K2.577.1%SourceLing 3.0 Flash Fin—Not directly comparable
DeepPlanning
Kimi K2.514.4%SourceLing 3.0 Flash Fin—Not directly comparable
Toolathlon
Kimi K2.527.8%SourceLing 3.0 Flash Fin—Not directly comparable
MCP Atlas
Kimi K2.529.5%SourceLing 3.0 Flash Fin—Not directly comparable
MCP-Tasks
Kimi K2.559.1%SourceLing 3.0 Flash Fin—Not directly comparable
WideResearch
Kimi K2.572.7%SourceLing 3.0 Flash Fin—Not directly comparable
BFCL v4
Kimi K2.568.3%SourceLing 3.0 Flash Fin—Not directly comparable
Gert Labs
Kimi K2.545.88%SourceLing 3.0 Flash Fin—Not directly comparable
ResearchClawBench
Kimi K2.514.0%SourceLing 3.0 Flash Fin—Not directly comparable
JobBench
Kimi K2.58.7%SourceLing 3.0 Flash Fin—Not directly comparable
Finance Agent v2
Kimi K2.5—Ling 3.0 Flash Fin59.8%SourceNot directly comparable
APEX-Agents
Kimi K2.5—Ling 3.0 Flash Fin29.2%SourceNot directly comparable
SpreadsheetBench 2
Kimi K2.5—Ling 3.0 Flash Fin21.8%SourceNot directly comparable
Coding
SWE-bench Verified
Kimi K2.576.8%SourceLing 3.0 Flash Fin—Not directly comparable
SWE-bench Verified*
Kimi K2.570.8%SourceLing 3.0 Flash Fin—Not directly comparable
LiveCodeBench v6
Kimi K2.585.0%SourceLing 3.0 Flash Fin—Not directly comparable
SWE-bench Pro
Kimi K2.550.7%SourceLing 3.0 Flash Fin—Not directly comparable
SWE Multilingual
Kimi K2.573%SourceLing 3.0 Flash Fin—Not directly comparable
SWE-Rebench
Kimi K2.558.5%SourceLing 3.0 Flash Fin—Not directly comparable
React Native Evals
Kimi K2.577.2%SourceLing 3.0 Flash Fin—Not directly comparable
NL2Repo
Kimi K2.532%SourceLing 3.0 Flash Fin—Not directly comparable
SciCode
Kimi K2.548.7%SourceLing 3.0 Flash Fin—Not directly comparable
Terminal-Bench 2.0
Kimi K2.550.8%SourceLing 3.0 Flash Fin—Not directly comparable
Reasoning
LongBench v2
Kimi K2.561%SourceLing 3.0 Flash Fin—Not directly comparable
Multimodal
MMMU
Kimi K2.584.3%SourceLing 3.0 Flash Fin—Not directly comparable
MMMU-Pro
Kimi K2.578.5%SourceLing 3.0 Flash Fin—Not directly comparable
RealWorldQA
Kimi K2.581.0%SourceLing 3.0 Flash Fin—Not directly comparable
OmniDocBench 1.5
Kimi K2.588.8%SourceLing 3.0 Flash Fin—Not directly comparable
Video-MME
Kimi K2.587.4%SourceLing 3.0 Flash Fin—Not directly comparable
Video-MME (with subtitle)
Kimi K2.587.4%SourceLing 3.0 Flash Fin—Not directly comparable
Video-MME (w/o subtitle)
Kimi K2.583.2%SourceLing 3.0 Flash Fin—Not directly comparable
MathVision
Kimi K2.584.2%SourceLing 3.0 Flash Fin—Not directly comparable
We-Math
Kimi K2.584.7%SourceLing 3.0 Flash Fin—Not directly comparable
DynaMath
Kimi K2.584.4%SourceLing 3.0 Flash Fin—Not directly comparable
SimpleVQA
Kimi K2.571.2%SourceLing 3.0 Flash Fin—Not directly comparable
MMLongBench-Doc
Kimi K2.558.5%SourceLing 3.0 Flash Fin—Not directly comparable
CC-OCR
Kimi K2.579.7%SourceLing 3.0 Flash Fin—Not directly comparable
AI2D_TEST
Kimi K2.590.8%SourceLing 3.0 Flash Fin—Not directly comparable
CountBench
Kimi K2.594.1%SourceLing 3.0 Flash Fin—Not directly comparable
RefCOCO (avg)
Kimi K2.587.8%SourceLing 3.0 Flash Fin—Not directly comparable
MMVU
Kimi K2.580.4%SourceLing 3.0 Flash Fin—Not directly comparable
VideoMMMU
Kimi K2.586.6%SourceLing 3.0 Flash Fin—Not directly comparable
MLVU (M-Avg)
Kimi K2.585.0%SourceLing 3.0 Flash Fin—Not directly comparable
CharXiv
Kimi K2.577.5%SourceLing 3.0 Flash Fin—Not directly comparable
Knowledge
GPQA
Kimi K2.587.6%SourceLing 3.0 Flash Fin—Not directly comparable
GPQA-D
Kimi K2.587.6%SourceLing 3.0 Flash Fin—Not directly comparable
SuperGPQA
Kimi K2.569.2%SourceLing 3.0 Flash Fin—Not directly comparable
MMLU-Pro
Kimi K2.587.1%SourceLing 3.0 Flash Fin—Not directly comparable
MMLU-Pro (Arcee)
Kimi K2.587.1%SourceLing 3.0 Flash Fin—Not directly comparable
MMLU-Redux
Kimi K2.594.5%SourceLing 3.0 Flash Fin—Not directly comparable
C-Eval
Kimi K2.594%SourceLing 3.0 Flash Fin—Not directly comparable
HLE
Kimi K2.530.1%SourceLing 3.0 Flash Fin—Not directly comparable
Multilingual
MMLU-ProX
Kimi K2.582.3%SourceLing 3.0 Flash Fin—Not directly comparable
NOVA-63
Kimi K2.556.0%SourceLing 3.0 Flash Fin—Not directly comparable
INCLUDE
Kimi K2.583.3%SourceLing 3.0 Flash Fin—Not directly comparable
PolyMath
Kimi K2.543.1%SourceLing 3.0 Flash Fin—Not directly comparable
MAXIFE
Kimi K2.572.8%SourceLing 3.0 Flash Fin—Not directly comparable
Instruction following
IFEval
Kimi K2.593.9%SourceLing 3.0 Flash Fin—Not directly comparable
Math
AIME 2025
Kimi K2.596.1%SourceLing 3.0 Flash Fin—Not directly comparable
AIME26
Kimi K2.595.8%SourceLing 3.0 Flash Fin—Not directly comparable
AIME25 (Arcee)
Kimi K2.596.3%SourceLing 3.0 Flash Fin—Not directly comparable
HMMT Feb 2025
Kimi K2.595.4%SourceLing 3.0 Flash Fin—Not directly comparable
HMMT Nov 2025
Kimi K2.591.1%SourceLing 3.0 Flash Fin—Not directly comparable
HMMT Feb 2026
Kimi K2.587.1%SourceLing 3.0 Flash Fin—Not directly comparable
MMAnswerBench
Kimi K2.581.8%SourceLing 3.0 Flash Fin—Not directly comparable
71 public results · 0 shared
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Last updated October 13, 2026