Chat turn cost
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
Claude Haiku 5.5 vs DeepSeek V4 Flash 0731
Updated October 7, 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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 1
- Claude Haiku 5.5 only
- 4
- DeepSeek V4 Flash 0731 only
- 41
- Like-for-like categories
- 0 / 8
Estimated: Claude Haiku 5.5. Conditional ranges do not establish rank confidence.How 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.
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K 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
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Claude Haiku 5.5
Claude Haiku 5.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
DeepSeek V4 Flash 0731 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
DeepSeek V4 Flash 0731 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
60.9Claude Haiku 5.5—DeepSeek V4 Flash 0731
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.
4 Claude Haiku 5.5 only
1 Shared
41 DeepSeek V4 Flash 0731 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- Claude Haiku 5.5
- 62.1
- Supported · #18/122
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- BenchAlign v5.8 lane · 2 vs 11 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Haiku 5.5
- 60.9
- Supported · #20/146
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- BenchAlign v5.8 lane · 1 vs 15 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Haiku 5.5
- 79.2
- Unranked · 2 rankable rows
- DeepSeek V4 Flash 0731
- 57.0
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Haiku 5.5
- Not ranked
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Haiku 5.5
- Not ranked
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- BenchAlign v5.8 lane · 1 vs 8 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Haiku 5.5
- Not ranked
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Haiku 5.5
- Not ranked
- DeepSeek V4 Flash 0731
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Haiku 5.5
- Not ranked
- DeepSeek V4 Flash 0731
- 79.9
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Claude Haiku 5.5 | DeepSeek V4 Flash 0731 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 62.1Supported · #18/122 | Not ranked | Not comparableBenchAlign v5.8 lane · 2 vs 11 public rows | Not comparable |
| Coding | 60.9Supported · #20/146 | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 15 public rows | Not comparable |
| Reasoning | 79.2Unranked · 2 rankable rows | 57.0Unranked · 4 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 8 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 79.9Unranked · 4 rankable rows | Not comparableProvisional lane · 0 vs 1 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.
Supported evidence per lane · 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
- Claude Haiku 5.5
- $0.00035
- Fits in one request
- DeepSeek V4 Flash 0731
- $0.00028
- Fits in one request
DeepSeek V4 Flash 0731 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Haiku 5.5
- $0.0065
- Fits in one request
- DeepSeek V4 Flash 0731
- $0.00784
- Fits in one request
Claude Haiku 5.5 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 Haiku 5.5
- $0.009
- Fits in one request
- DeepSeek V4 Flash 0731
- $0.00616
- Fits in one request
DeepSeek V4 Flash 0731 has the lower modeled cost
Costs use the listed standard API rates.
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.
SpecificationClaude Haiku 5.5DeepSeek V4 Flash 0731
Context window
Maximum documented context; output-token limits may be lower.
Claude Haiku 5.5
DeepSeek V4 Flash 0731
API model ID
Claude Haiku 5.5
claude-haiku-5-5
Anthropic Claude Haiku 5.5 model documentationDeepSeek V4 Flash 0731
deepseek-v4-flash
DeepSeek-V4.1-Flash releaseCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Haiku 5.5
$0.01 per 1M cached input tokens
Claude API pricingDeepSeek V4 Flash 0731
$0.0028 per 1M cached input tokens
Documented inputs
Claude Haiku 5.5
DeepSeek V4 Flash 0731
Documented outputs
Claude Haiku 5.5
DeepSeek V4 Flash 0731
Provider availability
Claude Haiku 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Haiku 5.5 model documentationDeepSeek V4 Flash 0731
Deprecated · DeepSeek API
DeepSeek-V4.1-Flash releaseReasoning profile
Claude Haiku 5.5
Reasoning
DeepSeek V4 Flash 0731
Reasoning
Weight access
Claude Haiku 5.5
Proprietary
DeepSeek V4 Flash 0731
Open Weight
License
Claude Haiku 5.5
Proprietary
DeepSeek V4 Flash 0731
Open Weight
Release date
Claude Haiku 5.5
2026-10-07
DeepSeek V4 Flash 0731
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
- Repository review: $0.0065 vs $0.00784. Cache-heavy agent loop: $0.009 vs $0.00616.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Haiku 5.5 or DeepSeek V4 Flash 0731?
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 Haiku 5.5 or DeepSeek V4 Flash 0731?
DeepSeek V4 Flash 0731 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Haiku 5.5 or DeepSeek V4 Flash 0731?
DeepSeek V4 Flash 0731 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Haiku 5.5 or DeepSeek V4 Flash 0731?
For the stated presets, chat costs $0.00035 on Claude Haiku 5.5 and $0.00028 on DeepSeek V4 Flash 0731; repository review costs $0.0065 and $0.00784; the cache-heavy agent loop costs $0.009 and $0.00616. Costs use the listed standard API rates.
Which has the larger context window, Claude Haiku 5.5 or DeepSeek V4 Flash 0731?
Both models list the same context window, 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence46 rows
Agentic
Terminal-Bench 4.0
Claude Haiku 5.539.20%SourceDeepSeek V4 Flash 0731—Not directly comparable
HLE w/ tools
Claude Haiku 5.557.4%SourceDeepSeek V4 Flash 073145.1%SourceClaude Haiku 5.5 leads this result
Terminal-Bench 2.0
Claude Haiku 5.5—DeepSeek V4 Flash 073156.9%SourceNot directly comparable
BrowseComp
Claude Haiku 5.5—DeepSeek V4 Flash 073173.2%SourceNot directly comparable
MCP Atlas
Claude Haiku 5.5—DeepSeek V4 Flash 073169%SourceNot directly comparable
Toolathlon
Claude Haiku 5.5—DeepSeek V4 Flash 073147.8%SourceNot directly comparable
Terminal-Bench 2.1
Claude Haiku 5.5—DeepSeek V4 Flash 073182.7%SourceNot directly comparable
CyberGym
Claude Haiku 5.5—DeepSeek V4 Flash 073176.7%SourceNot directly comparable
Toolathlon-Verified
Claude Haiku 5.5—DeepSeek V4 Flash 073170.3%SourceNot directly comparable
Agents' Last Exam
Claude Haiku 5.5—DeepSeek V4 Flash 073125.2%SourceNot directly comparable
AutomationBench
Claude Haiku 5.5—DeepSeek V4 Flash 073125.1%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Claude Haiku 5.5—DeepSeek V4 Flash 073167.0%SourceNot directly comparable
Coding
FrontierCode 1.1 Main
Claude Haiku 5.546.4%SourceDeepSeek V4 Flash 0731—Not directly comparable
LiveCodeBench Pass@1-COT
Claude Haiku 5.5—DeepSeek V4 Flash 073191.6%SourceNot directly comparable
Codeforces
Claude Haiku 5.5—DeepSeek V4 Flash 07313052.0SourceNot directly comparable
SWE-bench Verified
Claude Haiku 5.5—DeepSeek V4 Flash 073179%SourceNot directly comparable
SWE-bench Pro
Claude Haiku 5.5—DeepSeek V4 Flash 073152.6%SourceNot directly comparable
SWE Multilingual
Claude Haiku 5.5—DeepSeek V4 Flash 073173.3%SourceNot directly comparable
Terminal-Bench 2.0
Claude Haiku 5.5—DeepSeek V4 Flash 073156.9%SourceNot directly comparable
Terminal-Bench 2.1
Claude Haiku 5.5—DeepSeek V4 Flash 073182.7%SourceNot directly comparable
NL2Repo
Claude Haiku 5.5—DeepSeek V4 Flash 073154.2%SourceNot directly comparable
DeepSWE
Claude Haiku 5.5—DeepSeek V4 Flash 073154.4%SourceNot directly comparable
DSBench-FullStack
Claude Haiku 5.5—DeepSeek V4 Flash 073168.7%SourceNot directly comparable
DSBench-Hard
Claude Haiku 5.5—DeepSeek V4 Flash 073159.6%SourceNot directly comparable
VulcanBench v3
Claude Haiku 5.5—DeepSeek V4 Flash 073188.4%SourceNot directly comparable
OpenHarmony Bench
Claude Haiku 5.5—DeepSeek V4 Flash 073153.8%SourceNot directly comparable
LiveCodeBench (Vals)
Claude Haiku 5.5—DeepSeek V4 Flash 073187.3%SourceNot directly comparable
SWE-bench (Vals)
Claude Haiku 5.5—DeepSeek V4 Flash 073188.8%SourceNot directly comparable
Reasoning
MRCR 1M
Claude Haiku 5.5—DeepSeek V4 Flash 073178.7%SourceNot directly comparable
CorpusQA 1M
Claude Haiku 5.5—DeepSeek V4 Flash 073160.5%SourceNot directly comparable
ARC-AGI-1
Claude Haiku 5.5—DeepSeek V4 Flash 073189.00%SourceNot directly comparable
ARC-AGI-2
Claude Haiku 5.5—DeepSeek V4 Flash 073161.4%SourceNot directly comparable
Multimodal
Chartography (no tools)
Claude Haiku 5.546.4%SourceDeepSeek V4 Flash 0731—Not directly comparable
Knowledge
HLE w/o tools
Claude Haiku 5.545.9%SourceDeepSeek V4 Flash 0731—Not directly comparable
MMLU-Pro
Claude Haiku 5.5—DeepSeek V4 Flash 073186.2%SourceNot directly comparable
SimpleQA
Claude Haiku 5.5—DeepSeek V4 Flash 073134.1%SourceNot directly comparable
Chinese-SimpleQA
Claude Haiku 5.5—DeepSeek V4 Flash 073178.9%SourceNot directly comparable
GPQA
Claude Haiku 5.5—DeepSeek V4 Flash 073188.1%SourceNot directly comparable
GPQA-D
Claude Haiku 5.5—DeepSeek V4 Flash 073188.1%SourceNot directly comparable
HLE
Claude Haiku 5.5—DeepSeek V4 Flash 073134.8%SourceNot directly comparable
GPQA Diamond (Vals)
Claude Haiku 5.5—DeepSeek V4 Flash 073189.9%SourceNot directly comparable
MMLU-Pro (Vals)
Claude Haiku 5.5—DeepSeek V4 Flash 073186.2%SourceNot directly comparable
Math
HMMT Feb 2026
Claude Haiku 5.5—DeepSeek V4 Flash 073194.8%SourceNot directly comparable
IMOAnswerBench
Claude Haiku 5.5—DeepSeek V4 Flash 073188.4%SourceNot directly comparable
Apex
Claude Haiku 5.5—DeepSeek V4 Flash 073133.0%SourceNot directly comparable
Apex Shortlist
Claude Haiku 5.5—DeepSeek V4 Flash 073185.7%SourceNot directly comparable
46 public results · 1 shared
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Last updated October 7, 2026