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o1-pro vs Qwen3.8 Flash

Updated October 21, 2026. No benchmark has tested both models yet. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

o1-proOpenAI
Coding
No data
Overall
12.4
Output $/M
$600.00
Qwen3.8 FlashQwen
Coding
No data
Overall
No data
Output $/M
$0.47
vs $600.00 vs $0.47 per 1M output tokens. Qwen3.8 Flash is 1276.6x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
o1-pro not benchmarked, Qwen3.8 Flash not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
o1-pro $600.00 against Qwen3.8 Flash $0.47 per million output tokens, 1276.6x apart.
Context window
o1-pro takes 200K tokens, Qwen3.8 Flash 1M.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board measured
Coding benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
LiveBench codingNot measured87.4%Only Qwen3.8 Flash measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
AA Intelligence Index12.4Not measuredOnly o1-pro measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Agentic work benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
LiveBench researchNot measured74.6%Only Qwen3.8 Flash measured
LiveBench browserNot measured48.0%Only Qwen3.8 Flash measured
LiveBench long agenticNot measured37.1%Only Qwen3.8 Flash measured
Neither model has a result on the other 36 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
LiveBench reasoningNot measured87.4%Only Qwen3.8 Flash measured
ARC-AGI23.3%Not measuredOnly o1-pro measured
Neither model has a result on the other 19 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Web design benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
LiveBench designNot measured72.8%Only Qwen3.8 Flash measured
Neither model has a result on the other 8 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
General benchmarks for o1-pro and Qwen3.8 Flash
Benchmarko1-proQwen3.8 FlashLeader
LiveBench data analysisNot measured74.2%Only Qwen3.8 Flash measured
Neither model has a result on the other 45 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

o1-pro$0.450Fits in one request
Qwen3.8 Flash$0.0004Fits in one request

Qwen3.8 Flash costs less

Repository review

50K input + 3K output tokens

o1-pro$9.30Fits in one request
Qwen3.8 Flash$0.0089Fits in one request

Qwen3.8 Flash costs less

Agent loop

200K input + 10K output tokens

o1-pro$36.00Exceeds the context window
Qwen3.8 Flash$0.035Fits in one request

Qwen3.8 Flash costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of o1-pro and Qwen3.8 Flash
SpecificationOpenAI o1-proQwen3.8 Flash
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedMarch 19, 2025August 26, 2026
Context window200K1M
Input $/Mtok$150.00$0.15
Output $/Mtok$600.00$0.47
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is o1-pro better than Qwen3.8 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, o1-pro or Qwen3.8 Flash?

o1-pro costs $150.00 per million input tokens and $600.00 per million output tokens; Qwen3.8 Flash costs $0.15 and $0.47. Cost per solved task is known for neither of them.

Which has the bigger context window, o1-pro or Qwen3.8 Flash?

Qwen3.8 Flash, with 1M tokens against 200K.

Has any benchmark tested both o1-pro and Qwen3.8 Flash?

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead. Data as of October 21, 2026.

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