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Model comparison · accepted catalogue facts 2026-09-23

Qwen3 235B A22B Instruct 2507 vs Qwen3 235B A22B Thinking 2507

Qwen3 235B A22B Instruct 2507 has an equal-or-higher measured score and an equal-or-lower estimated price. Switching from Qwen3 235B A22B Thinking 2507 loses capability or fails a requirement. Review the migration checks. The reported score intervals overlap; this is not an established quality improvement.

Editorial comparison: Separate Instruct and Thinking checkpoints Inclusion does not recommend either model.

Qwen3 235B A22B Instruct 2507

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1419.8

Balanced effective USD / 1M tokens · lower is better

$0.153/M

Qwen3 235B A22B Thinking 2507

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1415.1

Balanced effective USD / 1M tokens · lower is better

$0.748/M

Compare · model decision

Choose two or three models

Inspect the differences, estimate your workload and keep the evidence. All standard catalogue models are available, including unrated ones.

Catalogue facts
2026-09-23

2 / 3 selected · 0 requirements
Open public comparison link
Public workload and requirements

These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.

A ↔ B

Qwen3 235B A22B Instruct 2507 has an equal-or-higher measured score and an equal-or-lower estimated price. Switching from Qwen3 235B A22B Thinking 2507 loses capability or fails a requirement. Review the migration checks. The reported score intervals overlap; this is not an established quality improvement.

Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.

What changes between these models

Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.

  • Qwen3 235B A22B Instruct 2507 · Meets the stated model requirements
  • Qwen3 235B A22B Thinking 2507 · Meets the stated model requirements
Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Qwen3 235B A22B Instruct 2507B Qwen3 235B A22B Thinking 2507
LMArena general score (Elo)1,419.81,415.1Δ vs A: -4.7 Elo
Score interval half-width (± Elo)2.576.55Δ vs A: +3.98 Elo
LMArena document score (Elo)UnknownUnknown
Estimated effective USD / 1M tokens$0.153125$0.7475Δ vs A: +0.594375 USD/M
Base input USD / 1M tokens$0.0875$0.23Δ vs A: +0.1425 USD/M
Base output USD / 1M tokens$0.35$2.3Δ vs A: +1.95 USD/M
Base cached-input USD / 1M tokens$0.0175Unknown
Context window (tokens)262,144131,072Δ vs A: -131,072 tokens
Output limit (tokens)235,929117,964Δ vs A: -117,965 tokens
ReasoningNot supportedSupportedΔ vs A: +1
Open weightsUnknownUnknown
Recorded licenceUnknownUnknown
Distinct sellers in the catalogue93Δ vs A: -6
Recorded retirement dateUnknownUnknown
6 shared measured facts
Shared measured facts. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Qwen3 235B A22B Instruct 2507B Qwen3 235B A22B Thinking 2507
Benchmark reasoning effortdefaultdefault
Input modalitiestexttext
Tool useSupportedSupportedΔ vs A: 0
Model providerQwenQwen
Serving precision differs across offersSupportedSupportedΔ vs A: 0
Retirement evidenceNone announced; not a guaranteeNone announced; not a guarantee

Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.

Complete price ladders and billing conditions

Qwen3 235B A22B Instruct 2507

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$0.0875$0.35$0.0175

Qwen3 235B A22B Thinking 2507

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$0.23$2.3Unknown
Migration preflight · compare each candidate with model A

Keeping Qwen3 235B A22B Instruct 2507 is a valid decision. No pairwise comparison certifies a drop-in replacement.

Qwen3 235B A22B Instruct 2507 → Qwen3 235B A22B Thinking 2507

Known loss or failed requirement

  • Context window: 262,144 → 131,072 tokens.
  • Output limit: 235,929 → 117,964 tokens.
  • Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.
Check alternatives to Qwen3 235B A22B Instruct 2507

Estimate a fixed request shape

Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.

0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.

  • Qwen3 235B A22B Instruct 2507Estimated total: $0.35 1,000 full attempts · base rates
  • Qwen3 235B A22B Thinking 2507Estimated total: $1.61 1,000 full attempts · base rates
Prompt and output sensitivity · sampled scenarios

Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.

Vary input; hold output, requests, cache and retries fixed.
Input tokensQwen3 235B A22B Instruct 2507Qwen3 235B A22B Thinking 2507Coverage
2,000$0.35Lowest known$1.61All computed
4,096$0.5334Lowest known$2.09208All computed
32,768$3.0422Lowest known$8.68664All computed
131,072$11.6438Lowest knownineligibleInput plus output exceeds the published context window.Incomplete
Vary output; hold input, requests, cache and retries fixed.
Output tokensQwen3 235B A22B Instruct 2507Qwen3 235B A22B Thinking 2507
128$0.2198$0.7544
2,048$0.8918$5.1704
8,192$3.0422$19.3016

Bring your observed evaluation results

JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.

Expected format
[{"model":"provider/exact-model-id","task":"support-answer","version":"rubric-1","attempts":100,"successes":84,"costUsd":2.4,"latencyMs":950}]

Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.

Keep the decision and its evidence

A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.

Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.

Saved local decisions · 0

No version 2 decision records are stored in this browser.

Questions this page answers

Is Qwen3 235B A22B Instruct 2507 a better-and-cheaper replacement for Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Instruct 2507 has an equal-or-higher measured score and an equal-or-lower estimated price. Switching from Qwen3 235B A22B Thinking 2507 loses capability or fails a requirement. Review the migration checks. The reported score intervals overlap; this is not an established quality improvement.

What is included in this comparison?

Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.

Can I compare a different workload or keep a decision record?

Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.

Evidence & Ask