Agentic
Like-for-like- Claude Sonnet 5
- 66.0
- Supported · #12/151
- Qwen3.8-Flash-Next
- 68.1
- Supported · #10/151
- Basis
- BenchAlign lane · 6 vs 6 public rows
- Reading
- Qwen3.8-Flash-Next leads · intervals overlap
Claude Sonnet 5 vs Qwen3.8-Flash-Next
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score estimate, 70.76 versus 59.42, but the 90% score intervals overlap. Treat that as a lead, not a settled 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.
Coding work
Code generation, repair, and software-engineering tasks
Claude Sonnet 5
Claude Sonnet 5 leads on the public coding lane, 64.2 to 57.9, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.8-Flash-Next
Qwen3.8-Flash-Next leads on the public agentic lane, 68.1 to 66, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
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.
17 Claude Sonnet 5 only
6 Shared
18 Qwen3.8-Flash-Next only
- Shared results
- 6
- Claude Sonnet 5 only
- 17
- Qwen3.8-Flash-Next only
- 18
- Like-for-like categories
- 4 / 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
Like-for-like- Claude Sonnet 5
- 64.2
- Supported · #13/183
- Qwen3.8-Flash-Next
- 57.9
- Supported · #32/183
- Basis
- BenchAlign lane · 9 vs 5 public rows
- Reading
- Claude Sonnet 5 leads · intervals overlap
Knowledge
Like-for-like- Claude Sonnet 5
- 67.1
- Supported · #20/181
- Qwen3.8-Flash-Next
- 56.5
- Supported · #52/181
- Basis
- BenchAlign lane · 6 vs 4 public rows
- Reading
- Claude Sonnet 5 leads · intervals overlap
Multimodal
Like-for-like- Claude Sonnet 5
- 77.5
- #13/48
- Qwen3.8-Flash-Next
- 83.3
- #7/48
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Qwen3.8-Flash-Next leads
Reasoning
Not comparable- Claude Sonnet 5
- 76.4
- Unranked · 2 rankable rows
- Qwen3.8-Flash-Next
- 76.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5
- Not ranked
- Qwen3.8-Flash-Next
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5
- Not ranked
- Qwen3.8-Flash-Next
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5
- Not ranked
- Qwen3.8-Flash-Next
- 88.0
- #32/120
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 5 | Qwen3.8-Flash-Next | Basis | Reading |
|---|---|---|---|---|
| Agentic | 66.0Supported · #12/151 | 68.1Supported · #10/151 | Like-for-likeBenchAlign lane · 6 vs 6 public rows | Qwen3.8-Flash-Next leads · intervals overlap |
| Coding | 64.2Supported · #13/183 | 57.9Supported · #32/183 | Like-for-likeBenchAlign lane · 9 vs 5 public rows | Claude Sonnet 5 leads · intervals overlap |
| Knowledge | 67.1Supported · #20/181 | 56.5Supported · #52/181 | Like-for-likeBenchAlign lane · 6 vs 4 public rows | Claude Sonnet 5 leads · intervals overlap |
| Multimodal | 77.5#13/48 | 83.3#7/48 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Qwen3.8-Flash-Next leads |
| Reasoning | 76.4Unranked · 2 rankable rows | 76.4Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 88.0#32/120 | 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) 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
Claude Sonnet 5: 57.4%Qwen3.8-Flash-Next: 35.9%Normalized gap 21.5Claude Sonnet 5 source Qwen3.8-Flash-Next sourceHLE w/o tools
Knowledge
Claude Sonnet 5: 43.2%Qwen3.8-Flash-Next: 35.9%Normalized gap 7.3Claude Sonnet 5 source Qwen3.8-Flash-Next sourceSWE Multilingual
Coding
Claude Sonnet 5: 78.3%Qwen3.8-Flash-Next: 81%Normalized gap 2.7Claude Sonnet 5 source Qwen3.8-Flash-Next sourceCharXiv
Multimodal
Claude Sonnet 5: 88.3%Qwen3.8-Flash-Next: 90.6%Normalized gap 2.3Claude Sonnet 5 source Qwen3.8-Flash-Next sourceSWE-bench Pro
Coding
Claude Sonnet 5: 63.2%Qwen3.8-Flash-Next: 62.5%Normalized gap 0.7Claude Sonnet 5 source Qwen3.8-Flash-Next 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
- Claude Sonnet 5
- $0.007
- Fits in one request
- Qwen3.8-Flash-Next
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.8-Flash-Next has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 5
- $0.13
- Fits in one request
- Qwen3.8-Flash-Next
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.8-Flash-Next has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 5
- $0.18
- Fits in one request
- Qwen3.8-Flash-Next
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Qwen3.8-Flash-Next 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.
SpecificationClaude Sonnet 5Qwen3.8-Flash-Next
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5
Qwen3.8-Flash-Next
API model ID
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewQwen3.8-Flash-Next
Qwen/Qwen3.8-Flash-Next
Qwen3.8-Flash-Next model cardCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingQwen3.8-Flash-Next
No comparable hosted API rate
Qwen3.8-Flash-Next model cardDocumented inputs
Claude Sonnet 5
text, image
Anthropic model overviewQwen3.8-Flash-Next
Not sourced
Documented outputs
Claude Sonnet 5
Qwen3.8-Flash-Next
Not sourced
Provider availability
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewQwen3.8-Flash-Next
Not sourced
Reasoning profile
Claude Sonnet 5
Reasoning
Qwen3.8-Flash-Next
Reasoning
Weight access
Claude Sonnet 5
Proprietary
Qwen3.8-Flash-Next
Open Weight
License
Claude Sonnet 5
Proprietary
Qwen3.8-Flash-Next
Open Weight
Release date
Claude Sonnet 5
2026-06-30
Qwen3.8-Flash-Next
2026-08-26
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
- Claude Sonnet 5 has the higher public score estimate, 70.76 versus 59.42, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Claude Sonnet 5 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 evidence41 rows
Agentic
Terminal-Bench 3.0
Claude Sonnet 514.6%SourceQwen3.8-Flash-Next—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceQwen3.8-Flash-Next—Not directly comparable
BrowseComp
Claude Sonnet 584.7%SourceQwen3.8-Flash-Next—Not directly comparable
HLE w/ tools
Claude Sonnet 557.4%SourceQwen3.8-Flash-Next—Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%SourceQwen3.8-Flash-Next—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 574.5%SourceQwen3.8-Flash-Next—Not directly comparable
CoWorkBench
Claude Sonnet 5—Qwen3.8-Flash-Next73.9%SourceNot directly comparable
JobBench
Claude Sonnet 5—Qwen3.8-Flash-Next55.7%SourceNot directly comparable
Agents' Last Exam
Claude Sonnet 5—Qwen3.8-Flash-Next51.2%SourceNot directly comparable
Toolathlon-Verified
Claude Sonnet 5—Qwen3.8-Flash-Next73.5%SourceNot directly comparable
AndroidWorld
Claude Sonnet 5—Qwen3.8-Flash-Next84.5%SourceNot directly comparable
OSWorld 2.0
Claude Sonnet 5—Qwen3.8-Flash-Next19.4%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 585.2%SourceQwen3.8-Flash-Next—Not directly comparable
SWE-bench Pro
Claude Sonnet 563.2%SourceQwen3.8-Flash-Next62.5%SourceClaude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%SourceQwen3.8-Flash-Next81%SourceQwen3.8-Flash-Next leads this result
SWE Multimodal
Claude Sonnet 528.1%SourceQwen3.8-Flash-Next—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceQwen3.8-Flash-Next—Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%SourceQwen3.8-Flash-Next—Not directly comparable
cursorBench32
Claude Sonnet 561.5%SourceQwen3.8-Flash-Next—Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 582.4%SourceQwen3.8-Flash-Next—Not directly comparable
SWE-bench (Vals)
Claude Sonnet 579.6%SourceQwen3.8-Flash-Next—Not directly comparable
NL2Repo
Claude Sonnet 5—Qwen3.8-Flash-Next48.1%SourceNot directly comparable
deepSwe
Claude Sonnet 5—Qwen3.8-Flash-Next58.7%SourceNot directly comparable
LiveCodeBench v6
Claude Sonnet 5—Qwen3.8-Flash-Next91.9%SourceNot directly comparable
Knowledge
HLE
Claude Sonnet 557.4%SourceQwen3.8-Flash-Next35.9%SourceClaude Sonnet 5 leads this result
HLE w/o tools
Claude Sonnet 543.2%SourceQwen3.8-Flash-Next35.9%SourceClaude Sonnet 5 leads this result
HLE-Verified
Claude Sonnet 531.0%SourceQwen3.8-Flash-Next—Not directly comparable
LABBench2
Claude Sonnet 580.1%SourceQwen3.8-Flash-Next—Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 588.9%SourceQwen3.8-Flash-Next—Not directly comparable
MMLU-Pro (Vals)
Claude Sonnet 587.5%SourceQwen3.8-Flash-Next—Not directly comparable
GPQA
Claude Sonnet 5—Qwen3.8-Flash-Next91.7%SourceNot directly comparable
GPQA-D
Claude Sonnet 5—Qwen3.8-Flash-Next91.7%SourceNot directly comparable
Multimodal
CharXiv
Claude Sonnet 588.3%SourceQwen3.8-Flash-Next90.6%SourceQwen3.8-Flash-Next leads this result
CharXiv w/o tools
Claude Sonnet 577%SourceQwen3.8-Flash-Next84.6%SourceQwen3.8-Flash-Next leads this result
Vision2Web
Claude Sonnet 5—Qwen3.8-Flash-Next64.0%SourceNot directly comparable
ERQA
Claude Sonnet 5—Qwen3.8-Flash-Next72.3%SourceNot directly comparable
LVBench
Claude Sonnet 5—Qwen3.8-Flash-Next76.6%SourceNot directly comparable
RealWorldQA
Claude Sonnet 5—Qwen3.8-Flash-Next88.5%SourceNot directly comparable
MathVision
Claude Sonnet 5—Qwen3.8-Flash-Next90.6%SourceNot directly comparable
MathVision w/ Python
Claude Sonnet 5—Qwen3.8-Flash-Next95.7%SourceNot directly comparable
Instruction following
IFBench
Claude Sonnet 5—Qwen3.8-Flash-Next81.3%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 5 or Qwen3.8-Flash-Next?
Claude Sonnet 5 has the higher public score estimate, 70.76 versus 59.42, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Claude Sonnet 5 or Qwen3.8-Flash-Next?
Claude Sonnet 5 leads the public coding lane, 64.2 to 57.9, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Sonnet 5 or Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next leads the public agentic tasks lane, 68.1 to 66, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Claude Sonnet 5 or Qwen3.8-Flash-Next?
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, Claude Sonnet 5 or Qwen3.8-Flash-Next?
Claude Sonnet 5 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 4, 2026
Watch Claude Sonnet 5 vs Qwen3.8-Flash-Next
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.