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Data as of September 27, 2026 · How the score is built

EstablishedProprietaryReasoning

Released Mar 4, 20261M context

Qwen3.5 Flash

Decision readingQwen3.5 Flash scores 45.5 out of 100 and ranks #93 of 194. This profile shows 6 source-displayable benchmark rows; its strongest eligible category is Knowledge at #80. API pricing is $0.1 input and $0.4 output per million tokens.

Released Mar 4, 2026 — see all recent releases

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Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

45.5/100

field median 50.2#93 of 194 ranked models

Public

#93of 194

Verified —

Price

$0.10input / $0.40 output

input median $0.97blended $0.25

Speed

Not measured

field median 91 tok/sTime to first token not measured

Context

1Mtokens

field median 256,000Reported for this model; direct source link not stored

Strongest published evidence

Knowledge ranks #80. Particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Validate before choosing

6 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.

Source-linked · 6 displayable benchmark rows

Follow model changes

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measured
Not measured
CodingRank #97 of 135Percentile 28thWeight 20%2 benchmarksVerified
26.5
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalWeight 12%0 benchmarksNot measured
Not measured
KnowledgeRank #80 of 158Percentile 50thWeight 12%2 benchmarksVerified
43.0
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathRank Not rankedWeight 5%2 benchmarksVerified
28.4

6 of 486 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. AgenticNot measured
  2. Coding2/2 verified
  3. ReasoningNot measured
  4. MultimodalNot measured
  5. Knowledge2/2 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math2/2 verified
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Qwen3.5 Flash category percentile values

  • AgenticNot eligible
  • Coding28th percentile
  • ReasoningNot eligible
  • MultimodalNot eligible
  • Knowledge50th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. AgenticNot ranked
  2. Coding#97/135
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#80/158
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding2 rows
Coding benchmark values, best verified comparison, weight, and source status
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore83.3%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap7.2 behindWeight8% ref. weight
Verified
Vals AI: LiveCodeBench leaderboard
SWE-bench (Vals)SWE-bench, Vals AI runScore64.4%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap32.6 behindWeightDisplay only
Verified
Vals AI: SWE-bench leaderboard
Knowledge2 rows
Knowledge benchmark values, best verified comparison, weight, and source status
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore84.1%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap8.3 behindWeight6% ref. weight
Verified
Vals AI: MMLU Pro leaderboard
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore82.8%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap12.7 behindWeight2% ref. weight
Verified
Vals AI: GPQA Diamond leaderboard
Math2 rows
Math benchmark values, best verified comparison, weight, and source status
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3Score6.207%Versus best verified row

Best verified: GPT-5.6 Sol · 89.000%

Gap82.8 behindWeightWeighted 30%
Benchmark exact
Epoch AI FrontierMath v2 leaderboard
FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4Score0.000%Versus best verified row

Best verified: GPT-6 Astra · 97.600%

Gap97.6 behindWeightWeighted 10%
Benchmark exact
Epoch AI FrontierMath v2 leaderboard

Bars run 0–100; the dark tick marks the best source-verified value

All 6 rows

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Qwen3.5 Flash · 45.5 score · $0.25 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

30405060708090100$0.50$1$5$10$25$50$100↘ frontierQwen3.5 Flash

Horizontal: blended price per million tokens, log scale · Vertical: public score

Price vs performance

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Mar 4, 2026 · you are here

    Qwen3.5 Flash

    Score 45.5 · $0.1 / $0.4

Base entry

Radar

Qwen3.5 Flash release history

Full release history

Radar confirmed these at the source. Use Qwen3.5 Flash in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not published
Context window
1M
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not disclosed by the provider
Availability
Not sourced yet
Cloud regions
Not tracked yet
Lifecycle
Established
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing record
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Qwen3.5 Flash ranks #93 of 194 on the public leaderboard with a score of 45.49/100. It does not yet have enough sourced coverage for a verified position.

Qwen3.5 Flash is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Tracked as unresolved. The official Qwen3.5-35B-A3B model card says Qwen3.5 Flash is the hosted version of that model with 1M context and built-in tools, but BenchLM has not yet sourced a clean exact-value benchmark table for the hosted API variant.

6 of 486 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Knowledge at #80, while its lowest eligible position is Coding at #97. particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Last updated September 27, 2026. Runtime fields remain blank until a sourced snapshot exists.

Questions

How does Qwen3.5 Flash perform overall in AI benchmarks?

Qwen3.5 Flash ranks #93 out of 194 models on the public BenchAlign leaderboard, with a score of 45.49/100. Its evidence status is Estimated, and this profile shows 6 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Qwen3.5 Flash good for knowledge and understanding?

Qwen3.5 Flash ranks #80 out of 158 eligible models for knowledge and understanding, with a public category score of 43/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.5 Flash good for coding and programming?

Qwen3.5 Flash ranks #97 out of 135 eligible models for coding and programming, with a public category score of 26.5/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.5 Flash good for mathematics?

Qwen3.5 Flash has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Does Qwen3.5 Flash have full benchmark coverage on BenchLM?

No. Qwen3.5 Flash currently has 6 source-displayable rows across 486 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Qwen3.5 Flash?

Qwen3.5 Flash has a reported context window of 1M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

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