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Home/Best GLM-5.3 Alternatives
Best alternative: Claude Fable 5Alternatives

Best GLM-5.3 Alternatives

Claude Fable 5 is the strongest alternative to GLM-5.3 — it scores 100 vs 91 on coding at $10/1M input (GLM-5.3 costs $1.4/1M). DeepSeek V4-Pro is the budget swap: $0.435/1M input is 69% cheaper. Kimi K3 is the top open-weight option if you want a model you can self-host.

Last verified Aug 27, 2026/Model data modified Aug 27, 2026
Rankings refresh dailyScored on 6 criteriaNo paid rankings
AnthropicPremium
Input cost
$10.00/1M
Context
1M tokens
Speed
Deliberate

Clear recommendation block

The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.

Best overall model

Claude Fable 5

View
Why this recommendation

Claude Fable 5 is the safest overall answer here when you want the strongest default instead of the lowest list price.

AnthropicPremium
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Price
$10.00/1M
Context
1M tokens
Best budget model

Mistral: Mistral Nemo

View
Why this recommendation

Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.

MistralBudget
Best for
Teams needing a cheap, fast, multilingual workhorse for classification, summarization, or light coding tasks at scale.
Price
$0.02/1M
Context
131k tokens
Best for speed

GLM-5.3

View
Why this recommendation

GLM-5.3 is the better pick when response speed matters more than maximum reasoning depth.

Z.aiBudget
Best for
Agentic engineering and security work on open weights
Price
$1.40/1M
Context
1M tokens

Why this page recommends it

Claude Fable 5 beats GLM-5.3 on coding (100 vs 91) at $10/1M input tokens.

DeepSeek V4-Pro cuts input cost by 69% ($0.435 vs $1.4/1M) while scoring 93/100 on coding.

Kimi K3 is open-weight — self-host it or run it via low-cost API providers at $3/1M input.

Decision notes

Choose Claude Fable 5 when you want the closest overall replacement — it targets the hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning.

Choose DeepSeek V4-Pro when token volume matters more than peak quality — it is 69% cheaper on input.

Staying with Z.ai? GLM-5.2 is the strongest in-house switch at $1.4/1M input.

Interactive decision lab

Test the recommendation against your priority

Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.

#1Claude Fable 591 pts
#2Claude Mythos 590 pts
#3Kimi K388 pts
#4DeepSeek V4-Pro83 pts
#5GLM-5.381 pts
Quality first

Claude Fable 5

Anthropic / Premium / Jun 9, 2026

91

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.

Cost
$10.00/1M
$50.00/1M out
Speed
Deliberate
2/5 score
Context
1M tokens
input window
View model
Data-backed recommendation
Avoid this pick if

You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.

Recommended comparisons

The fastest way to see where the recommendation shifts when your priority changes.

Z.aiBudgetBest alternative: Claude Fable 5

GLM-5.3

Same price as GLM-5.2, far stronger on agents and security.

Best use case
Agentic engineering and security work on open weights
Input
$1.40/1M
Pricing
Budget
Speed
Balanced
Context
1M tokens
Open weightsAgenticSecurity
AnthropicPremiumOption 2

Claude Fable 5

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

Best use case
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Input
$10.00/1M
Pricing
Premium
Speed
Deliberate
Context
1M tokens
Coding leaderSWE-Bench Pro #1Mythos-class
DeepSeekBudgetOption 3

DeepSeek V4-Pro

Best open-weights flagship — near-frontier coding at a tenth of the price.

Best use case
Frontier-level coding and reasoning on a budget
Input
$0.43/1M
Pricing
Budget
Speed
Balanced
Context
1M tokens
Open weightsCodingReasoning
MoonshotPremiumOption 4

Kimi K3

Closest Chinese challenger to the frontier — #4 overall on intelligence.

Best use case
Frontier-level reasoning and agentic coding
Input
$3.00/1M
Pricing
Premium
Speed
Deliberate
Context
1M tokens
Open weightsReasoningFlagship
Z.aiBudgetOption 5

GLM-5.2

Top open-weights coder — beats GPT-5.5 at a sixth of the cost.

Best use case
Budget agentic coding at scale
Input
$1.40/1M
Pricing
Budget
Speed
Balanced
Context
1M tokens
Open weightsCodingBudget
AnthropicPremiumOption 6

Claude Mythos 5

The frontier ceiling — same model as Fable 5, safeguards lifted, partner-only.

Best use case
Frontier cybersecurity research, autonomous vulnerability discovery, and the absolute capability ceiling
Input
$10.00/1M
Pricing
Premium
Speed
Deliberate
Context
1M tokens
FrontierRestricted accessCybersecurity

Side-by-side specs

Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.

ModelInputOutputEst. monthContextSpeedCodingWritingResearch
Claude Fable 5Anthropic$10.00/1M$50.00/1M$2001M tokensDeliberate10098100
GLM-5.3Z.ai$1.40/1M$4.40/1M$231M tokensBalanced917982
DeepSeek V4-ProDeepSeek$0.43/1M$0.87/1M$6.091M tokensBalanced938085
Kimi K3Moonshot$3.00/1M$15.00/1M$601M tokensDeliberate969093

Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.

The case for each model

What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.

Claude Fable 5

Best alternative: Claude Fable 5Anthropic

Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.

Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate

What people actually use it for

  • Autonomous agents that plan, write, run, and debug across an entire codebase with minimal supervision
  • Whole-repo refactors and PR review where accuracy outranks latency or cost
  • Frontier reasoning over 1M-token corpora — security audits, legal discovery, scientific synthesis

Where it wins

  • 80.3% SWE-Bench Pro — the new #1, up from Opus 4.8's 69.2% and GPT-5.5's 58.6%
  • 1932 on GDPval-AA, ahead of Opus 4.8 (1890) and GPT-5.5 (1769)
  • 1M-token context at standard pricing, 128K max output per request
  • Mythos-class capability released for general use with new cyber-risk safeguards

Where it falls down

  • Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25)
  • Deliberate pace; not for latency-sensitive interactive apps
  • Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access)

Skip it if

You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.

Our verdict

The strongest coding and reasoning model you can actually use today. 80.3% SWE-Bench Pro is an 11-point leap over Opus 4.8 — the biggest single-release jump of 2026. It costs 2× Opus 4.8, so use it for the hardest agentic and engineering work and keep Opus 4.8 or Sonnet for everyday volume.

Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.

GLM-5.3

Z.ai

Z.ai's newest flagship, aimed squarely at software engineering, autonomous agents and cybersecurity — and the first open-weights model to beat Claude Mythos 5 on a security benchmark.

Input
$1.40/1M
Output
$4.40/1M
Context
1M tokens
Speed
Balanced

What people actually use it for

  • Long-horizon autonomous engineering tasks where GLM-5.2 ran out of headroom
  • Offensive and defensive security tooling — 84.5% on CyberGym, ahead of Claude Mythos 5
  • Self-hosted or coding-plan deployments that need frontier-adjacent quality at open-weights pricing

Where it wins

  • Huge agentic gains over GLM-5.2: Terminal-Bench 3.0 from 4.6 to 28.3, DeepSWE v1.1 from 46.2 to 66.9, SWE-Marathon v1.1 from 19.4 to 42.5
  • 84.5% on CyberGym, narrowly ahead of Claude Mythos 5 at 83.8%; ExploitBench more than doubled from 24.4% to 54.4%
  • 88.2% on Terminal-Bench 2.1 with a 1M token context window

Where it falls down

  • No published SWE-bench Verified score, so it is absent from the benchmark most buyers compare on
  • Priced identically to GLM-5.2 at $1.40/$4.40 — the upgrade is capability, not value

Skip it if

Your procurement process requires a SWE-bench Verified figure, or you need the closed-frontier reasoning ceiling.

Our verdict

The clear upgrade over GLM-5.2 at the same price — take it unless you specifically need a published SWE-bench Verified number to sign off on. The security benchmark lead over Mythos 5 is the genuinely new thing here.

Released August 14, 2026. Z.ai list pricing is $1.40/$4.40, the same rate as GLM-5.2; resellers discount from that list. Also available through the GLM Coding Plan from $18/mo. Reported GPQA Diamond 91.7% and Artificial Analysis Intelligence Index 59.5.

DeepSeek V4-Pro

DeepSeek

DeepSeek's 1.6T-parameter (49B active) MoE flagship with hybrid sparse attention — near-frontier coding and reasoning at roughly a tenth of closed-rival pricing, MIT-licensed open weights.

Input
$0.43/1M
Output
$0.87/1M
Context
1M tokens
Speed
Balanced

What people actually use it for

  • Repository-level coding — 80.6% SWE-bench Verified (self-reported), the top open-weights score at release
  • Competitive-programming-grade reasoning (Codeforces rating 3206)
  • Self-hosted frontier capability under an MIT license

Where it wins

  • 80.6% SWE-bench Verified (self-reported) — reported as tied with Gemini 3.1 Pro
  • 93.5% LiveCodeBench and Codeforces 3206 — elite competitive-coding results
  • 1M context with 384K max output at $0.87/1M output — an order of magnitude cheaper than closed frontier models

Where it falls down

  • Independent harnesses report much lower agentic scores than the self-reported numbers; trails GPT-5.6 and Opus-class on hard agentic evals
  • Peak-hour surge pricing doubles rates, a price increase is announced, and it's text-only (no vision)

Skip it if

You need vision input, verified agentic performance, or predictable pricing (surge pricing and an announced increase loom).

Our verdict

The open-weights frontier flagship of 2026. Self-reported numbers flatter it and independent agentic scores land lower, but even discounted it's the most capability per dollar in the directory's upper tier — with MIT-licensed weights.

Open-weight preview April 24; GA ~July 20, 2026. Off-peak pricing verified on api-docs.deepseek.com; Beijing-business-hours surge doubles it. Legacy deepseek-chat/reasoner endpoints retired July 24, 2026.

Kimi K3

Moonshot

Moonshot's 2.8-trillion-parameter multimodal reasoning flagship with always-on thinking — the largest open-weight model ever released and the closest Chinese challenger to the Western frontier.

Input
$3.00/1M
Output
$15.00/1M
Context
1M tokens
Speed
Deliberate

What people actually use it for

  • Hardest reasoning tasks — #4 of all models on AA Intelligence Index v4.1 (57.1), ahead of Claude Opus 4.8
  • Agentic coding at 81.2 FrontierSWE and 88.3 Terminal-Bench 2.0 (Moonshot-reported)
  • 1M-context research synthesis with always-on extended thinking

Where it wins

  • AA Intelligence Index v4.1: 57.1 — #4 overall, behind only Claude Fable 5 and GPT-5.6 Sol, ahead of Claude Opus 4.8
  • FrontierSWE 81.2 and Terminal-Bench 2.0 88.3 — frontier-grade agentic coding numbers
  • Open weights (July 26, 2026) — at 2.8T parameters, the largest open-weight release in history

Where it falls down

  • Most expensive Chinese-lab model ever ($3/$15) with always-on thinking driving high output-token burn and slow responses
  • 2.8T size makes self-hosting impractical despite open weights; consumer signups were paused July 19 over GPU capacity

Skip it if

You need fast responses or predictable output costs — always-on thinking burns tokens.

Our verdict

The first Chinese model to genuinely crowd the Western frontier — #4 on aggregate intelligence ahead of Opus 4.8. The always-on thinking makes it slow and output-heavy, so cost per task runs above the sticker price. A serious Opus-class alternative if latency isn't critical.

Released July 16, 2026; open weights July 26. Cache-hit input $0.30/1M. Subscriptions: Adagio (free) to Vivace $199/mo; full 1M context only on Allegro ($99) and up. New signups paused July 19 near GPU capacity, reopening in batches.

Explore related decisions

Z.ai
GLM-5.3Same price as GLM-5.2, far stronger on agents and security.Read guide
Anthropic
Claude Fable 5New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.Read guide
Comparison
GLM-5.3 vs DeepSeek V4-ProGLM-5.3 vs DeepSeek V4-Pro — see exactly which wins on SWE-bench coding, price per 1M tokens, context window, and speed, with a clear verdict for every use…Read guide
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Best Claude Fable 5 AlternativesLooking for a Claude Fable 5 alternative? Compare 3 rivals on real capability scores, price per 1M tokens, and context size — including cheaper and open-weight…Read guide
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Best Cheap AIThe cheapest AI models ranked by real value: GPT-4o Mini at $0.15/1M, Gemini Flash at $0.075/1M, DeepSeek V3 at $0.07/1M. Find which budget AI is actually…Read guide
Tool
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Quick links

Browse all modelsCompare pricingView GLM-5.3View Claude Fable 5View DeepSeek V4-Pro

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FAQ

What is the best alternative to GLM-5.3?

Claude Fable 5 is the strongest overall alternative. It scores 100/100 on coding (GLM-5.3: 91/100) and costs $10/1M input vs $1.4/1M. New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

What is the cheapest good alternative to GLM-5.3?

DeepSeek V4-Pro at $0.435/1M input — 69% cheaper than GLM-5.3's $1.4/1M. It scores 93/100 on coding, so expect a quality step down on the hardest tasks.

Is there an open-source alternative to GLM-5.3?

Yes — Kimi K3 is the strongest open-weight replacement for GLM-5.3, scoring 96/100 on coding against GLM-5.3's 91/100. You can self-host it or run it through hosted APIs at $3/1M input (GLM-5.3 costs $1.4/1M), with no per-seat subscription. Self-hosting trades the licence saving for infrastructure you have to run, so it pays off at sustained volume rather than for occasional use.

What is the best Z.ai alternative to GLM-5.3?

GLM-5.2 — same provider, same API surface, $1.4/1M input vs $1.4/1M. Top open-weights coder — beats GPT-5.5 at a sixth of the cost.

Is GLM-5.3 still worth using in 2026?

The clear upgrade over GLM-5.2 at the same price — take it unless you specifically need a published SWE-bench Verified number to sign off on.