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Celeris-1 vs Qwen3 235B-A22B (Reasoning)

Updated October 14, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Celeris logo

Celeris

28.3/100

Estimated · Public rank #189

Conditional range 13.9–42.6

Model B
Alibaba logo

Alibaba

—

Evidence status unavailable

90% interval unavailable

Shared results
1
Celeris-1 only
3
Qwen3 235B-A22B (Reasoning) only
10
Like-for-like categories
0 / 8
Estimated: Celeris-1. Conditional ranges do not establish rank confidence.How the comparison works

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.

  • Long documents

    Prompts that approach the documented context limit

    Qwen3 235B-A22B (Reasoning)

    Qwen3 235B-A22B (Reasoning) has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Qwen3 235B-A22B (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Qwen3 235B-A22B (Reasoning) is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

    Confidence: rate-fallback
  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

11.0Celeris-1—Qwen3 235B-A22B (Reasoning)

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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.

Agentic

Not comparable
Celeris-1
7.1
Estimated · #120/124
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 1 public rows
Reading
Not comparable

Coding

Not comparable
Celeris-1
11.0
Estimated · #141/149
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Celeris-1
52.0
Unranked · 3 rankable rows
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Celeris-1
Not ranked
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Celeris-1
28.5
Supported · #157/181
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
BenchAlign v5.8 lane · 1 vs 4 public rows
Reading
Not comparable

Multilingual

Not comparable
Celeris-1
Not ranked
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Celeris-1
Not ranked
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Celeris-1
Not ranked
Qwen3 235B-A22B (Reasoning)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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

Celeris-1
$0.00055
Does not fit in one request
Qwen3 235B-A22B (Reasoning)
API rate not published
Fits in one request

Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Celeris-1
$0.0121
Does not fit in one request
Qwen3 235B-A22B (Reasoning)
API rate not published
Fits in one request

Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Celeris-1
$0.051
Does not fit in one request
Cached input priced at the published list-input rate
Qwen3 235B-A22B (Reasoning)
API rate not published
Does not fit in one request
Cached-input rate unavailable

Celeris-1 does not fit this workload in one request. Qwen3 235B-A22B (Reasoning) does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3 235B-A22B (Reasoning) has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Celeris-1

131,072 tokens

Celeris-1 model guide

Qwen3 235B-A22B (Reasoning)

128K

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Celeris-1

Not published

Celeris API pricing

Qwen3 235B-A22B (Reasoning)

No comparable hosted API rate

Provider availability

Celeris-1

Generally Available · Celeris OpenAI-compatible API (United States)

Celeris availability

Qwen3 235B-A22B (Reasoning)

Not sourced

Reasoning profile

Celeris-1

Non-Reasoning

Qwen3 235B-A22B (Reasoning)

Reasoning

Weight access

Celeris-1

Proprietary

Qwen3 235B-A22B (Reasoning)

Open Weight

License

Celeris-1

Proprietary

Qwen3 235B-A22B (Reasoning)

Open Weight

Release date

Celeris-1

2026-07-22

Qwen3 235B-A22B (Reasoning)

2025-04-29

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
Qwen3 235B-A22B (Reasoning) has the larger documented window (128K).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Celeris-1 or Qwen3 235B-A22B (Reasoning)?

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, Celeris-1 or Qwen3 235B-A22B (Reasoning)?

Qwen3 235B-A22B (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Celeris-1 or Qwen3 235B-A22B (Reasoning)?

Qwen3 235B-A22B (Reasoning) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Celeris-1 or Qwen3 235B-A22B (Reasoning)?

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, Celeris-1 or Qwen3 235B-A22B (Reasoning)?

Qwen3 235B-A22B (Reasoning) has the larger documented context window: 128K, compared with 131,072 tokens.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence14 rows

Agentic

  • BFCL v3

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)70.8%
    Source

    Not directly comparable

Coding

  • LiveCodeBench v5

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)70.7%
    Source

    Not directly comparable

Reasoning

  • DROP

    Celeris-181.4%
    Source
    Qwen3 235B-A22B (Reasoning)—

    Not directly comparable

Knowledge

  • MMLU-Pro

    Celeris-175.9%
    Source
    Qwen3 235B-A22B (Reasoning)—

    Not directly comparable

  • MMLU-Redux

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)92.7%
    Source

    Not directly comparable

  • GPQA

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)71.1%
    Source

    Not directly comparable

  • C-Eval

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)89.6%
    Source

    Not directly comparable

  • MMMLU

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)84.3%
    Source

    Not directly comparable

Multilingual

  • INCLUDE

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)78.7%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Celeris-180.8%
    Source
    Qwen3 235B-A22B (Reasoning)83.4%
    Source

    Qwen3 235B-A22B (Reasoning) leads this result

Math

  • GSM8K

    Celeris-193.7%
    Source
    Qwen3 235B-A22B (Reasoning)—

    Not directly comparable

  • MATH-500

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)98%
    Source

    Not directly comparable

  • AIME 2024

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)85.7%
    Source

    Not directly comparable

  • AIME 2025

    Celeris-1—
    Qwen3 235B-A22B (Reasoning)81.5%
    Source

    Not directly comparable

14 public results · 1 shared

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Last updated October 14, 2026