Coding
Directional only- Claude 3.5 Sonnet
- 49.0
- DeepSeek V4 Flash 0731
- 68.8
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start free briefUpdated August 13, 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.
2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Prompts that approach the documented context limit
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
50K fresh input + 3K output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
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
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
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. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | Claude 3.5 Sonnet | DeepSeek V4 Flash 0731 | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 49.0 | 68.8 | Directional only1 vs 2 rows | Directional only |
| Knowledge | 59.4 | 55.3 | Directional only1 vs 4 rows | Directional only |
| Agentic | Not measured | 63.8 | Not comparable0 vs 2 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | 1.6 | 94.8 | Not comparable2 vs 1 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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
GPQA
Knowledge
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.
1K fresh input + 500 output tokens
DeepSeek V4 Flash 0731 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
DeepSeek V4 Flash 0731 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude 3.5 Sonnet
200K
DeepSeek V4 Flash 0731
Claude 3.5 Sonnet
Not sourced
DeepSeek V4 Flash 0731
deepseek-v4-flash
DeepSeek V4 Flash 0731 updateA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude 3.5 Sonnet
Not published
DeepSeek V4 Flash 0731
$0.0028 per 1M cached input tokens
Claude 3.5 Sonnet
Not sourced
DeepSeek V4 Flash 0731
Claude 3.5 Sonnet
Not sourced
DeepSeek V4 Flash 0731
Claude 3.5 Sonnet
Not sourced
DeepSeek V4 Flash 0731
Public Beta · DeepSeek API
DeepSeek V4 Flash 0731 updateClaude 3.5 Sonnet
Non-Reasoning
DeepSeek V4 Flash 0731
Reasoning
Claude 3.5 Sonnet
Proprietary
DeepSeek V4 Flash 0731
Proprietary
Claude 3.5 Sonnet
Proprietary
DeepSeek V4 Flash 0731
Proprietary
Claude 3.5 Sonnet
2024-06-01
DeepSeek V4 Flash 0731
2026-07-31
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.0
Not directly comparable
BrowseComp
Not directly comparable
HLE w/ tools
Not directly comparable
MCP Atlas
Not directly comparable
Toolathlon
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
CyberGym
Not directly comparable
Toolathlon-Verified
Not directly comparable
Agents' Last Exam
Not directly comparable
AutomationBench
Not directly comparable
SWE-bench Verified
DeepSeek V4 Flash 0731 leads this result
LiveCodeBench Pass@1-COT
Not directly comparable
Codeforces
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
NL2Repo
Not directly comparable
deepSwe
Not directly comparable
DSBench-FullStack
Not directly comparable
DSBench-Hard
Not directly comparable
GPQA
DeepSeek V4 Flash 0731 leads this result
MMLU-Pro
Not directly comparable
SimpleQA
Not directly comparable
Chinese-SimpleQA
Not directly comparable
GPQA-D
Not directly comparable
HLE
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
HMMT Feb 2026
Not directly comparable
IMOAnswerBench
Not directly comparable
Apex
Not directly comparable
Apex Shortlist
Not directly comparable
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.
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.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet and $0.00028 on DeepSeek V4 Flash 0731; repository review costs $0.195 and $0.00784; the cache-heavy agent loop costs $0.81 and $0.00616. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
DeepSeek V4 Flash 0731 has the larger documented context window: 1M, compared with 200K.
Last updated August 13, 2026
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