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ModelScale

Qwen3.8-Flash-Next

Alibaba · Open Weight · rank 76 · bench-align-v5

Self-hosted
Canonical idqwen3-8-flash-next
Overall score57.02
Context window262K tokens
Release date2026-08-26
Access typeOpen Weight
Blended $/1MUnavailable75% input / 25% output

Capability shape

Seven axes from the ranking source. A missing axis is drawn as a gap.

Capability evidence

Agentic41
Coding55
Knowledge52.2
Reasoning75.8
Multimodal & Grounded83.3
Instruction Following88
MathUnavailable

Runtime service evidence

Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.

Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.

Evidence key: Observed

Runtime measurements
MeasurementValueObservedLast goodEvidence
Time to first token40.61 s2026-09-172026-09-17
Throughput53 tok/s2026-09-172026-09-17

Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.

Endpoint and price matrix

Every published price component, including cache reads and writes.

Price components
ComponentUSDEvidence
Input / 1M tokensUnavailable
Output / 1M tokensUnavailable
Cache read / 1M tokensUnavailable
Cache write / 1M tokensUnavailable
Blended / 1M (75% input / 25% output)Unavailable
Self-hosted listingQwen publishes Qwen3.8-Flash-Next under the Qwen Community 1.0 license for self-hosting and does not publish a distinct first-party hosted token rate for this exact experimental checkpoint. BenchLM represents the open-weight row as self-host/free-per-token before infrastructure costs. Qwen Cloud's production Qwen3.8-Flash is a separate model based on this architecture, so this row does not inherit its price or default 1M context.No hosted token rate was published for this model, so its per-token price is unavailable rather than zero.

Workload-aware monthly cost example

10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.

Modelled monthly costUnavailableThe applicable input rate is unavailable.
Modelled tokensUnavailable
Open the simulatorChange this workload

Benchmark record

38 matched benchmark rows with their published value, unit, and provenance.

Knowledge

Knowledge benchmarks
BenchmarkValueTasksDifficultyProvenance
GPQA
Graduate-Level Google-Proof Q&A
91.7448 questionsGraduate levelGPQA: A Graduate-Level Google-Proof Q&A Benchmark
GPQA-D
GPQA Diamond
91.7Graduate-level science questionsGraduate levelTrinity-Large-Thinking: Scaling an Open Source Frontier Agent
HLE
Humanity's Last Exam
35.9Expert-level questionsFrontier expert levelHumanity's Last Exam
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index
39.9Cross-benchmark intelligence indexDisplay-only external referenceArtificial Analysis
AA-GPQA Diamond
Artificial Analysis GPQA Diamond
92.3Graduate-level science questionsGraduate-level science reasoningArtificial Analysis GPQA Diamond Benchmark Leaderboard
AA-HLE
Artificial Analysis Humanity's Last Exam
38.0Expert-level questionsFrontier expert reasoningArtificial Analysis Humanity's Last Exam Benchmark Leaderboard
AA-Omniscience Index
Artificial Analysis Omniscience Index
-9.7Knowledge questionsBroad factual knowledgeAA-Omniscience: Knowledge and Hallucination Benchmark
AA-Omniscience Accuracy
Artificial Analysis Omniscience Accuracy
24.5Knowledge questionsBroad knowledgeArtificial Analysis model benchmarks
AA-Omniscience Hallucination Rate
Artificial Analysis Omniscience Hallucination Rate
45.3Knowledge questionsFactualityArtificial Analysis model benchmarks
HLE w/o tools
Humanity's Last Exam without tools
35.9Expert-level questionsFrontier expert levelIntroducing GPT-5.4 mini and nano

Coding

Coding benchmarks
BenchmarkValueTasksDifficultyProvenance
LiveCodeBench v6
LiveCodeBench v6
91.9Fresh programming problemsCompetitive programming levelLiveCodeBench official repository and release documentation
SWE-bench Pro
SWE-bench Pro
62.51,865 repository problemsLong-horizon professional engineeringSWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
SWE Multilingual
SWE Multilingual
81Multilingual software-engineering tasksProfessional software engineeringMiniMax M2.7: Early Echoes of Self-Evolution
NL2Repo
NL2Repo
48.1Natural language to repository tasksSystem-level software comprehensionMiniMax M2.7: Early Echoes of Self-Evolution
AA Coding Index
Artificial Analysis Coding Index
73.0Cross-benchmark coding indexDisplay-only external referenceArtificial Analysis model leaderboards
AA-SciCode
Artificial Analysis SciCode
50.6Scientific coding subproblemsScientific programmingArtificial Analysis SciCode Benchmark Leaderboard
DeepSWE
DeepSWE
58.7113 software engineering tasks across 91 repositories and 5 languagesLong-horizon software engineeringDeepSWE benchmark blog

Reasoning

Reasoning benchmarks
BenchmarkValueTasksDifficultyProvenance
AA-LCR
Artificial Analysis Long Context Reasoning
79.7Long-context reasoning tasksLong-context reasoningArtificial Analysis model benchmarks
CritPt
Critical Physics Tasks
11.1Research-level physics questionsResearch-level physics reasoningCritPt Benchmark Leaderboard

Instruction Following

Instruction Following benchmarks
BenchmarkValueTasksDifficultyProvenance
IFBench
Instruction Following Benchmark
81.3BenchLM

Agentic

Agentic benchmarks
BenchmarkValueTasksDifficultyProvenance
AA Briefcase
Artificial Analysis Briefcase
1587Professional knowledge-work tasksProfessional workArtificial Analysis Briefcase Benchmark Leaderboard
GDPval-AA
GDPval-AA
1648Agentic real-world work tasksProfessional agentic workflowsDeepSeek-V4 Technical Report
GDPval-AA
GDPval-AA normalized
57.4Economically valuable tasksProfessional agentic workflowsArtificial Analysis model benchmarks
OSWorld 2.0
OSWorld 2.0
19.4108 long-horizon computer-use workflowsLong-horizon professional workflowsOSWorld2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
JobBench
JobBench
55.7130 tasks across 35 occupationsProfessional multi-source workflowsJobBench: Aligning Agent Work With Human Will
AndroidWorld
AndroidWorld
84.5Android app workflowsComplex mobile task completionGLM-5V-Turbo
Toolathlon-Verified
Toolathlon-Verified
73.5Verified multi-tool workflowsAdvanced tool useKimi K3: Open Frontier Intelligence
Agents' Last Exam
Agents' Last Exam
51.2Agent tasksAdvanced agentic workDeepSeek V4 Flash 0731 update
CoWorkBench
CoWorkBench
73.9Long-horizon professional workflowsCross-domain professional workQwen3.8-Max: A New Bar for Coding and Cowork

Multimodal & Grounded

Multimodal & Grounded benchmarks
BenchmarkValueTasksDifficultyProvenance
AA-MMMU-Pro
Artificial Analysis MMMU-Pro
79.8Multimodal academic reasoningFrontier multimodalArtificial Analysis MMMU-Pro Benchmark Leaderboard
MathVision w/ Python
MathVision with Python
95.7Visual mathematics problems with PythonAdvanced multimodal mathematicsKimi K3: Open Frontier Intelligence
RealWorldQA
RealWorldQA
88.5Real-world visual question answeringGeneral visual reasoningQwen3.6 launch benchmarks
MathVision
MathVision
90.6Visually grounded math problemsAdvanced multimodal mathematicsQwen3.6 launch benchmarks
ERQA
ERQA
72.3Evidence-based visual QAGrounded multimodal reasoningQwen3.6 launch benchmarks
LVBench
LVBench
76.6Long-form video question answeringExtended temporal reasoningQwen3.8-Max: A New Bar for Coding and Cowork
Vision2Web
Vision2Web
64.0Screenshot-to-web tasksMultimodal web generationGLM-5V-Turbo
CharXiv
CharXiv Reasoning
90.6Scientific chart reasoningScientific visualization reasoningCharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
CharXiv w/o tools
CharXiv Reasoning without tools
84.6Scientific chart reasoning (tool-free)Scientific visualization reasoningCharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

Lifecycle and limitations log

Lifecycle events the source associates with this model, plus what this profile does not claim.

No lifecycle event references this model.

That is not evidence the model has no lifecycle plan — only that this source published none.

What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-09-17 17:17 UTC.