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BenchLM

Quasar 438B vs Step 5 Preview

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.

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

Model A
Quasar 438B

Multiverse Computing

—

Evidence status unavailable

90% interval unavailable

StepFun logo
Model B
Step 5 Preview

StepFun

—

Evidence status unavailable

90% interval unavailable

Updated September 21, 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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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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Quasar 438B

    Quasar 438B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Step 5 Preview

    Step 5 Preview has the lower estimated token cost for this stated workload. Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Quasar 438B

    Quasar 438B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Quasar 438B and Step 5 Preview are 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

    Quasar 438B and Step 5 Preview are not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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.

—Quasar 438B—Step 5 Preview

Not comparable · BenchAlign

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.

Open the coding leaderboardShortlist models for this job

What is actually comparable

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

Shared results
2
Quasar 438B only
0
Step 5 Preview only
20
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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
Quasar 438B
Not ranked
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 1 vs 11 public rows
Reading
Not comparable

Coding

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 1 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
Quasar 438B
73.4
Unranked · 2 rankable rows
Step 5 Preview
78.5
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
61.2
#28/49
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 0 vs 2 public rows
Reading
Not comparable

Multilingual

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Quasar 438B
Not ranked
Step 5 Preview
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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

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

Quasar 438B
$0.0015
Fits in one request
Step 5 Preview
$0.00235
Fits in one request

Quasar 438B has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Quasar 438B
$0.0354
Fits in one request
Step 5 Preview
$0.0581
Fits in one request

Quasar 438B has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Quasar 438B
$0.15
Fits in one request
Cached input priced at the published list-input rate
Step 5 Preview
$0.057
Fits in one request

Step 5 Preview has the lower modeled cost

Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

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

Reasoning profile

Quasar 438B

Reasoning

Step 5 Preview

Reasoning

Weight access

Quasar 438B

Proprietary

Step 5 Preview

Pending

License

Quasar 438B

Proprietary

Step 5 Preview

Pending

Release date

Quasar 438B

2026-09-02

Step 5 Preview

2026-09-20

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
Repository review: $0.0354 vs $0.0581. Cache-heavy agent loop: $0.15 vs $0.057.
Context tradeoff
Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

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

Browse raw public benchmark evidence22 rows

Agentic

  • Terminal-Bench 2.1

    Quasar 438B69.3%
    Source
    Step 5 Preview85.0%
    Source

    Step 5 Preview leads this result

  • Terminal-Bench 4.0

    Quasar 438B—
    Step 5 Preview33.30%
    Source

    Not directly comparable

  • CyberGym

    Quasar 438B—
    Step 5 Preview84.7%
    Source

    Not directly comparable

  • AutomationBench

    Quasar 438B—
    Step 5 Preview44.0%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Quasar 438B—
    Step 5 Preview74.1%
    Source

    Not directly comparable

  • MCP Atlas

    Quasar 438B—
    Step 5 Preview85.6%
    Source

    Not directly comparable

  • JobBench

    Quasar 438B—
    Step 5 Preview59.0%
    Source

    Not directly comparable

  • APEX-Agents

    Quasar 438B—
    Step 5 Preview37.8%
    Source

    Not directly comparable

  • DRACO

    Quasar 438B—
    Step 5 Preview83.3%
    Source

    Not directly comparable

  • BrowseComp

    Quasar 438B—
    Step 5 Preview88.7%
    Source

    Not directly comparable

  • Agents' Last Exam

    Quasar 438B—
    Step 5 Preview29.5%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Quasar 438B69.3%
    Source
    Step 5 Preview85.0%
    Source

    Step 5 Preview leads this result

  • DeepSWE

    Quasar 438B—
    Step 5 Preview67.7%
    Source

    Not directly comparable

  • SciCode

    Quasar 438B—
    Step 5 Preview58.9%
    Source

    Not directly comparable

  • ProgramBench

    Quasar 438B—
    Step 5 Preview80.5%
    Source

    Not directly comparable

  • sweMarathon

    Quasar 438B—
    Step 5 Preview72.7%
    Source

    Not directly comparable

  • MLS-Bench Lite

    Quasar 438B—
    Step 5 Preview40.5%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Quasar 438B—
    Step 5 Preview20.9%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Quasar 438B—
    Step 5 Preview60.3%
    Source

    Not directly comparable

  • MMMU-Pro

    Quasar 438B—
    Step 5 Preview76%
    Source

    Not directly comparable

Knowledge

  • GPQA-D

    Quasar 438B—
    Step 5 Preview93.5%
    Source

    Not directly comparable

  • HLE

    Quasar 438B—
    Step 5 Preview46.5%
    Source

    Not directly comparable

Questions

Which is better, Quasar 438B or Step 5 Preview?

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, Quasar 438B or Step 5 Preview?

Quasar 438B and Step 5 Preview are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Quasar 438B or Step 5 Preview?

Quasar 438B and Step 5 Preview are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Quasar 438B or Step 5 Preview?

For the stated presets, chat costs $0.0015 on Quasar 438B and $0.00235 on Step 5 Preview; repository review costs $0.0354 and $0.0581; the cache-heavy agent loop costs $0.15 and $0.057. Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Quasar 438B or Step 5 Preview?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 21, 2026

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