Agentic
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- 56.5
- Supported · #33/152
- Basis
- BenchAlign lane · 1 vs 11 public rows
- Reading
- Not comparable
A.X K2 vs DeepSeek V4 Pro 0813
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.
6 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.
Long documents
Prompts that approach the documented context limit
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
A.X K2 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
A.X K2 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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: listed-rates
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.
4 A.X K2 only
6 Shared
34 DeepSeek V4 Pro 0813 only
- Shared results
- 6
- A.X K2 only
- 4
- DeepSeek V4 Pro 0813 only
- 34
- 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- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- 51.9
- Supported · #49/151
- Basis
- BenchAlign lane · 3 vs 15 public rows
- Reading
- Not comparable
Reasoning
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- 60.3
- #15/20
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- 59.8
- Estimated · #38/183
- Basis
- BenchAlign lane · 2 vs 8 public rows
- Reading
- Not comparable
Math
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- 80.4
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- A.X K2
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
| Category | A.X K2 | DeepSeek V4 Pro 0813 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 56.5Supported · #33/152 | Not comparableBenchAlign lane · 1 vs 11 public rows | Not comparable |
| Coding | Not ranked | 51.9Supported · #49/151 | Not comparableBenchAlign lane · 3 vs 15 public rows | Not comparable |
| Reasoning | Not ranked | 60.3#15/20 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 59.8Estimated · #38/183 | Not comparableBenchAlign lane · 2 vs 8 public rows | Not comparable |
| Math | Not ranked | 80.4Unranked · 4 rankable rows | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 1 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.
HLE
Knowledge
A.X K2: 27.8%DeepSeek V4 Pro 0813: 42.7%Normalized gap 14.9A.X K2 source DeepSeek V4 Pro 0813 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
- A.X K2
- Self-hosted; infrastructure cost varies
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.00087
- Fits in one request
A.X K2 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- A.X K2
- Self-hosted; infrastructure cost varies
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.02436
- Fits in one request
A.X K2 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- A.X K2
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
- DeepSeek V4 Pro 0813
- $0.01812
- Fits in one request
A.X K2 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.
SpecificationA.X K2DeepSeek V4 Pro 0813
Context window
Maximum documented context; output-token limits may be lower.
A.X K2
DeepSeek V4 Pro 0813
API model ID
A.X K2
skt/A.X-K2
SK Telecom A.X K2 model cardDeepSeek V4 Pro 0813
deepseek-v4-pro
DeepSeek models and pricingCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
A.X K2
No comparable hosted API rate
SK Telecom A.X K2 model cardDeepSeek V4 Pro 0813
$0.003625 per 1M cached input tokens
Documented inputs
A.X K2
Not sourced
DeepSeek V4 Pro 0813
Documented outputs
A.X K2
Not sourced
DeepSeek V4 Pro 0813
Provider availability
A.X K2
Not sourced
DeepSeek V4 Pro 0813
Generally Available · DeepSeek API
DeepSeek-V4.1-Flash releaseReasoning profile
A.X K2
Reasoning
DeepSeek V4 Pro 0813
Reasoning
Weight access
A.X K2
Open Weight
DeepSeek V4 Pro 0813
Proprietary
License
A.X K2
Open Weight
DeepSeek V4 Pro 0813
Proprietary
Release date
A.X K2
2026-07-29
DeepSeek V4 Pro 0813
2026-08-13
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
- DeepSeek V4 Pro 0813 has the larger documented window (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 evidence44 rows
Agentic
Terminal-Bench 2.1
A.X K236.0%SourceDeepSeek V4 Pro 081387.9%SourceDeepSeek V4 Pro 0813 leads this result
Terminal-Bench 2.0
A.X K2—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
BrowseComp
A.X K2—DeepSeek V4 Pro 081383.4%SourceNot directly comparable
HLE w/ tools
A.X K2—DeepSeek V4 Pro 081360.0%SourceNot directly comparable
MCP Atlas
A.X K2—DeepSeek V4 Pro 081373.6%SourceNot directly comparable
Toolathlon
A.X K2—DeepSeek V4 Pro 081351.8%SourceNot directly comparable
CyberGym
A.X K2—DeepSeek V4 Pro 081383.3%SourceNot directly comparable
Toolathlon-Verified
A.X K2—DeepSeek V4 Pro 081374.1%SourceNot directly comparable
Agents' Last Exam
A.X K2—DeepSeek V4 Pro 081325.7%SourceNot directly comparable
AutomationBench
A.X K2—DeepSeek V4 Pro 081331.8%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
A.X K2—DeepSeek V4 Pro 081354.7%SourceNot directly comparable
Coding
LiveCodeBench v6
A.X K284.0%SourceDeepSeek V4 Pro 0813—Not directly comparable
SciCode
A.X K241%SourceDeepSeek V4 Pro 0813—Not directly comparable
Terminal-Bench 2.1
A.X K236.0%SourceDeepSeek V4 Pro 081387.9%SourceDeepSeek V4 Pro 0813 leads this result
LiveCodeBench Pass@1-COT
A.X K2—DeepSeek V4 Pro 081393.5%SourceNot directly comparable
Codeforces
A.X K2—DeepSeek V4 Pro 08133206.0SourceNot directly comparable
SWE-bench Verified
A.X K2—DeepSeek V4 Pro 081380.6%SourceNot directly comparable
SWE-bench Pro
A.X K2—DeepSeek V4 Pro 081355.4%SourceNot directly comparable
SWE Multilingual
A.X K2—DeepSeek V4 Pro 081376.2%SourceNot directly comparable
Terminal-Bench 2.0
A.X K2—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
Vibe Code Bench
A.X K2—DeepSeek V4 Pro 081349.93%SourceNot directly comparable
NL2Repo
A.X K2—DeepSeek V4 Pro 081361.5%SourceNot directly comparable
DeepSWE
A.X K2—DeepSeek V4 Pro 081362.7%SourceNot directly comparable
DSBench-FullStack
A.X K2—DeepSeek V4 Pro 081371.1%SourceNot directly comparable
DSBench-Hard
A.X K2—DeepSeek V4 Pro 081367.2%SourceNot directly comparable
OpenHarmony Bench
A.X K2—DeepSeek V4 Pro 081359.0%SourceNot directly comparable
LiveCodeBench (Vals)
A.X K2—DeepSeek V4 Pro 081387.5%SourceNot directly comparable
SWE-bench (Vals)
A.X K2—DeepSeek V4 Pro 081396.4%SourceNot directly comparable
Reasoning
Knowledge
HLE
A.X K227.8%SourceDeepSeek V4 Pro 081342.7%SourceDeepSeek V4 Pro 0813 leads this result
GPQA-D
A.X K285.6%SourceDeepSeek V4 Pro 081390.1%SourceDeepSeek V4 Pro 0813 leads this result
MMLU-Pro
A.X K2—DeepSeek V4 Pro 081387.5%SourceNot directly comparable
SimpleQA
A.X K2—DeepSeek V4 Pro 081357.9%SourceNot directly comparable
Chinese-SimpleQA
A.X K2—DeepSeek V4 Pro 081384.4%SourceNot directly comparable
GPQA
A.X K2—DeepSeek V4 Pro 081390.1%SourceNot directly comparable
GPQA Diamond (Vals)
A.X K2—DeepSeek V4 Pro 081392.4%SourceNot directly comparable
MMLU-Pro (Vals)
A.X K2—DeepSeek V4 Pro 081387.0%SourceNot directly comparable
Math
AIME26
A.X K297.1%SourceDeepSeek V4 Pro 0813—Not directly comparable
Apex
A.X K245.8%SourceDeepSeek V4 Pro 081338.3%SourceA.X K2 leads this result
Apex Shortlist
A.X K288.6%SourceDeepSeek V4 Pro 081390.2%SourceDeepSeek V4 Pro 0813 leads this result
HMMT Feb 2026
A.X K2—DeepSeek V4 Pro 081395.2%SourceNot directly comparable
IMOAnswerBench
A.X K2—DeepSeek V4 Pro 081389.8%SourceNot directly comparable
Instruction following
IFBench
A.X K275.9%SourceDeepSeek V4 Pro 0813—Not directly comparable
Frequently asked questions
Which is better, A.X K2 or DeepSeek V4 Pro 0813?
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, A.X K2 or DeepSeek V4 Pro 0813?
A.X K2 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, A.X K2 or DeepSeek V4 Pro 0813?
A.X K2 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, A.X K2 or DeepSeek V4 Pro 0813?
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, A.X K2 or DeepSeek V4 Pro 0813?
DeepSeek V4 Pro 0813 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 10, 2026
Watch A.X K2 vs DeepSeek V4 Pro 0813
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.