Coding
Like-for-like- DeepSeek V4 Flash 0731
- 68.8
- Muse Spark
- 67.8
- Weighted basis
- 2 vs 2 rows
- Reading
- DeepSeek V4 Flash 0731 leads
DeepSeek V4 Flash 0731 vs Muse Spark
Updated 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.
6 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Coding work
Code generation, repair, and software-engineering tasks
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads on the same 2 weighted benchmark rows.
Confidence: limited
Long documents
Prompts that approach the documented context limit
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
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.
27 DeepSeek V4 Flash 0731 only
6 Shared
18 Muse Spark only
- Shared results
- 6
- DeepSeek V4 Flash 0731 only
- 27
- Muse Spark only
- 18
- Like-for-like categories
- 1 / 8
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
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.
Agentic
Directional only- DeepSeek V4 Flash 0731
- 63.8
- Muse Spark
- 59.0
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Knowledge
Directional only- DeepSeek V4 Flash 0731
- 55.3
- Muse Spark
- 50.4
- Weighted basis
- 4 vs 1 rows
- Reading
- Directional only
Reasoning
Not comparable- DeepSeek V4 Flash 0731
- Not measured
- Muse Spark
- 42.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Math
Not comparable- DeepSeek V4 Flash 0731
- 94.8
- Muse Spark
- 32.9
- Weighted basis
- 1 vs 2 rows
- Reading
- Not comparable
Multilingual
Not comparable- DeepSeek V4 Flash 0731
- Not measured
- Muse Spark
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- DeepSeek V4 Flash 0731
- Not measured
- Muse Spark
- 82.5
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Instruction following
Not comparable- DeepSeek V4 Flash 0731
- Not measured
- Muse Spark
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | DeepSeek V4 Flash 0731 | Muse Spark | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 68.8 | 67.8 | Like-for-like2 vs 2 rows | DeepSeek V4 Flash 0731 leads |
| Agentic | 63.8 | 59.0 | Directional only2 vs 1 rows | Directional only |
| Knowledge | 55.3 | 50.4 | Directional only4 vs 1 rows | Directional only |
| Reasoning | Not measured | 42.5 | Not comparable0 vs 1 rows | Not comparable |
| Math | 94.8 | 32.9 | Not comparable1 vs 2 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 82.5 | Not comparable0 vs 2 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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
DeepSeek V4 Flash 0731: 34.8%Muse Spark: 50.4%Normalized gap 15.6DeepSeek V4 Flash 0731 source Muse Spark sourceTerminal-Bench 2.0
Agentic
DeepSeek V4 Flash 0731: 56.9%Muse Spark: 59%Normalized gap 2.1DeepSeek V4 Flash 0731 source Muse Spark sourceSWE-bench Verified
Coding
DeepSeek V4 Flash 0731: 79%Muse Spark: 77.4%Normalized gap 1.6DeepSeek V4 Flash 0731 source Muse Spark sourceSWE-bench Pro
Coding
DeepSeek V4 Flash 0731: 52.6%Muse Spark: 52.4%Normalized gap 0.2DeepSeek V4 Flash 0731 source Muse Spark 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
- DeepSeek V4 Flash 0731
- $0.00028
- Fits in one request
- Muse Spark
- API rate not published
- Fits in one request
Muse Spark has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- DeepSeek V4 Flash 0731
- $0.00784
- Fits in one request
- Muse Spark
- API rate not published
- Fits in one request
Muse Spark has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- DeepSeek V4 Flash 0731
- $0.00616
- Fits in one request
- Muse Spark
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Muse Spark 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.
SpecificationDeepSeek V4 Flash 0731Muse Spark
Context window
Maximum documented context; output-token limits may be lower.
DeepSeek V4 Flash 0731
Muse Spark
262K
API model ID
DeepSeek V4 Flash 0731
deepseek-v4-flash
DeepSeek V4 Flash 0731 updateMuse Spark
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
DeepSeek V4 Flash 0731
$0.0028 per 1M cached input tokens
Muse Spark
No comparable hosted API rate
Documented inputs
DeepSeek V4 Flash 0731
Muse Spark
Not sourced
Documented outputs
DeepSeek V4 Flash 0731
Muse Spark
Not sourced
Provider availability
DeepSeek V4 Flash 0731
Public Beta · DeepSeek API
DeepSeek V4 Flash 0731 updateMuse Spark
Not sourced
Reasoning profile
DeepSeek V4 Flash 0731
Reasoning
Muse Spark
Reasoning
Weight access
DeepSeek V4 Flash 0731
Proprietary
Muse Spark
Proprietary
License
DeepSeek V4 Flash 0731
Proprietary
Muse Spark
Proprietary
Release date
DeepSeek V4 Flash 0731
2026-07-31
Muse Spark
2026-04-08
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 Flash 0731 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 evidence51 rows
Agentic
Terminal-Bench 2.0
DeepSeek V4 Flash 073156.9%SourceMuse Spark59%SourceMuse Spark leads this result
BrowseComp
DeepSeek V4 Flash 073173.2%SourceMuse Spark—Not directly comparable
HLE w/ tools
DeepSeek V4 Flash 073145.1%SourceMuse Spark—Not directly comparable
MCP Atlas
DeepSeek V4 Flash 073169%SourceMuse Spark—Not directly comparable
Toolathlon
DeepSeek V4 Flash 073147.8%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.1
DeepSeek V4 Flash 073182.7%SourceMuse Spark—Not directly comparable
CyberGym
DeepSeek V4 Flash 073176.7%SourceMuse Spark43.5%SourceDeepSeek V4 Flash 0731 leads this result
Toolathlon-Verified
DeepSeek V4 Flash 073170.3%SourceMuse Spark—Not directly comparable
Agents' Last Exam
DeepSeek V4 Flash 073125.2%SourceMuse Spark—Not directly comparable
AutomationBench
DeepSeek V4 Flash 073125.1%SourceMuse Spark—Not directly comparable
τ²-bench results
DeepSeek V4 Flash 0731—Muse Spark91.5%SourceNot directly comparable
DeepSearchQA
DeepSeek V4 Flash 0731—Muse Spark74.8%SourceNot directly comparable
Claw-Eval
DeepSeek V4 Flash 0731—Muse Spark63.8%SourceNot directly comparable
Coding
LiveCodeBench Pass@1-COT
DeepSeek V4 Flash 073191.6%SourceMuse Spark—Not directly comparable
Codeforces
DeepSeek V4 Flash 07313052.0SourceMuse Spark—Not directly comparable
SWE-bench Verified
DeepSeek V4 Flash 073179%SourceMuse Spark77.4%SourceDeepSeek V4 Flash 0731 leads this result
SWE-bench Pro
DeepSeek V4 Flash 073152.6%SourceMuse Spark52.4%SourceDeepSeek V4 Flash 0731 leads this result
SWE Multilingual
DeepSeek V4 Flash 073173.3%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.0
DeepSeek V4 Flash 073156.9%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.1
DeepSeek V4 Flash 073182.7%SourceMuse Spark—Not directly comparable
NL2Repo
DeepSeek V4 Flash 073154.2%SourceMuse Spark—Not directly comparable
deepSwe
DeepSeek V4 Flash 073154.4%SourceMuse Spark—Not directly comparable
DSBench-FullStack
DeepSeek V4 Flash 073168.7%SourceMuse Spark—Not directly comparable
DSBench-Hard
DeepSeek V4 Flash 073159.6%SourceMuse Spark—Not directly comparable
LiveCodeBench Pro
DeepSeek V4 Flash 0731—Muse Spark80.0%SourceNot directly comparable
Vibe Code Bench
DeepSeek V4 Flash 0731—Muse Spark19.67%SourceNot directly comparable
Reasoning
Knowledge
MMLU-Pro
DeepSeek V4 Flash 073186.2%SourceMuse Spark—Not directly comparable
SimpleQA
DeepSeek V4 Flash 073134.1%SourceMuse Spark—Not directly comparable
Chinese-SimpleQA
DeepSeek V4 Flash 073178.9%SourceMuse Spark—Not directly comparable
GPQA
DeepSeek V4 Flash 073188.1%SourceMuse Spark—Not directly comparable
GPQA-D
DeepSeek V4 Flash 073188.1%SourceMuse Spark89.5%SourceMuse Spark leads this result
HLE
DeepSeek V4 Flash 073134.8%SourceMuse Spark50.4%SourceMuse Spark leads this result
HLE w/o tools
DeepSeek V4 Flash 0731—Muse Spark42.8%SourceNot directly comparable
HealthBench Hard
DeepSeek V4 Flash 0731—Muse Spark42.8%SourceNot directly comparable
MedXpertQA (Text)
DeepSeek V4 Flash 0731—Muse Spark52.6%SourceNot directly comparable
Math
HMMT Feb 2026
DeepSeek V4 Flash 073194.8%SourceMuse Spark—Not directly comparable
IMOAnswerBench
DeepSeek V4 Flash 073188.4%SourceMuse Spark—Not directly comparable
Apex
DeepSeek V4 Flash 073133.0%SourceMuse Spark—Not directly comparable
Apex Shortlist
DeepSeek V4 Flash 073185.7%SourceMuse Spark—Not directly comparable
FrontierMath v2 (Tiers 1-3)
DeepSeek V4 Flash 0731—Muse Spark39.000%SourceNot directly comparable
FrontierMath v2 (Tier 4)
DeepSeek V4 Flash 0731—Muse Spark14.600%SourceNot directly comparable
Multimodal
CharXiv
DeepSeek V4 Flash 0731—Muse Spark86.4%SourceNot directly comparable
MMMU-Pro
DeepSeek V4 Flash 0731—Muse Spark80.4%SourceNot directly comparable
ERQA
DeepSeek V4 Flash 0731—Muse Spark64.7%SourceNot directly comparable
SimpleVQA
DeepSeek V4 Flash 0731—Muse Spark71.3%SourceNot directly comparable
ScreenSpot Pro
DeepSeek V4 Flash 0731—Muse Spark84.1%SourceNot directly comparable
ZeroBench
DeepSeek V4 Flash 0731—Muse Spark33.0%SourceNot directly comparable
MedXpertQA (MM)
DeepSeek V4 Flash 0731—Muse Spark78.4%SourceNot directly comparable
Frequently asked questions
Which is better, DeepSeek V4 Flash 0731 or Muse Spark?
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, DeepSeek V4 Flash 0731 or Muse Spark?
DeepSeek V4 Flash 0731 leads the like-for-like coding comparison across 2 shared weighted benchmark rows.
Which is better for agentic tasks, DeepSeek V4 Flash 0731 or Muse Spark?
The current agentic tasks 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.
Which costs less, DeepSeek V4 Flash 0731 or Muse Spark?
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, DeepSeek V4 Flash 0731 or Muse Spark?
DeepSeek V4 Flash 0731 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated August 13, 2026
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